Mathematics Books

Book SynopsisWhy is it that incredibly unlikely phenomena actually happen quite regularly and why should we, in fact, expect such things to happen? Here, in this highly original book - aimed squarely at anyone with an interest in coincidences, probability or gambling - eminent statistician David Hand answers this question by weaving together various strands of probability into a unified explanation, which he calls the improbability principle.This is a book that will appeal not only to those who love stories about startling coincidences and extraordinarily rare events, but also to those who are interested in how a single bold idea links areas as diverse as gambling, the weather, airline disasters and creative writing as well as the origin of life and even the universe. The Improbability Principle will change your perspective on how the world works and tell you what the Bible code and Shakespeare have in common, how to win the lottery, why Apple''s song shuffling was made less random to seem more random. Oh and why lightning does in fact strike twice...Trade ReviewA hugely entertaining eye-opener about how misuse of statistics can skew our view of the world * Daily Mail *Lively and lucid . . . an intensely useful (as well as a remarkably entertaining) book . . . * Salon *In my experience, it is very rare to find a book that is both erudite and entertaining. Yet The Improbability Principle is such a book. Surely this cannot be due to chance alone! -- Hal Varian, Google’s Chief EconomistAn elegant, astoundingly clear and enjoyable combination of subtle statistical thinking and real-world events. -- Andrew Dilnot, co-author of 'The Numbers Game'As someone who happened to meet his future wife on a plane, on an airline he rarely used, I wholeheartedly endorse David Hand’s fascinating guide to improbability, a subject which affects the lives of all, yet until now has lacked a coherent exposition of its underlying principles. -- Gordon Woo, catastrophist at Risk Management Solutions

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Book SynopsisAimed at the Key Stage 1 Level, this workbook features many mathematical exercises providing practice in basic computational skills, including money. It covers such topics as Recognition of values up to 20, Number Stories 11-20, Recognition of 10p and Picture Problems.

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Book SynopsisMental Arithmetic provides rich and varied practice to develop pupils' essential maths skills at Key Stage 2 and beyond. Mental Arithmetic 4 Answers contains answers to all the questions included in the Mental Arithmetic 4 pupil book.

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Book SynopsisThe weird and wonderful quest for unfathomably large numbersTrade Review‘A wonderful new book… if you love journeying into imagined mathematical worlds and simply exploring, then [this book] is pure, unadulterated escapism… brilliant.’ -- New Scientist‘We are taken on an amazing adventure… [with] witty humour and fascinating facts… a comprehensive read that I would struggle to find fault in and for anyone with a passion for maths, or a knack for numbers, I couldn’t recommend it enough!’ -- Astronomy Ireland‘The brilliant combination of an accomplished science writer and a young mathematical prodigy has resulted in page after page that oozes enthusiasm, clarity and intrigue.’ -- Bobby Seagull, on Weirder MathsTable of ContentsIntroduction 1 Of Sand and Stars 2 At the Limits of Reality 3 Maths Unbound 4 Up, Up and Away 5 G Whizz 6 Conway’s Chains 7 Ackermann and the Power of Recursion 8 Figure This – If You Can 9 Infinite Matters 10 Growing Fast 11 Does Not Compute! 12 The Strange World of the Googologist 13 Bridge to Beyond 14 The Biggest Number of All Acknowledgements Bibliography Useful websites and webpages References

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Book SynopsisA beautiful and original book in which renowned thinker and geometrist Keith Critchlow focuses on flowers as examples of symmetry and geometry. Fully illustrated with hand-drawn geometric patterns.Trade Review'I've been looking at plants all my life and it's one of my great pleasures, Keith Critchlow's book adds new dimensions to this enjoyment and shows how number and geometry are made manifest in the forms that we see in every garden, in wild flowers and in the cut flowers that decorate our rooms … The plentiful illustrations help make this a book of inspiration and insight.'-- Dr Rupert Sheldrake'This is less a book for what we call "reading" than a book to be lived with as a delightful and instructive companion for a long time. It is a fascinating book, full of things useful and pleasing to know. And I admire the honest circularity of its plot that begins in mystery, passes through much knowledge, and returns again (in fact again and again) to mystery.'-- Wendell Berry'I have been waiting thirty-five years for this book.'-- Julian Barnard, author of Bach Flower Remedies: Form and Function'Like many people, I've been eagerly awaiting the publication of this book, and I have to say that it has been a real delight finally to read its inspirational thoughts and also to contemplate the large number of beautiful images and geometrical diagrams that is contains … The Hidden Geometry of Flowers is a wonderful gift to the growing number of people who, dissatisfied with the impoverished and disenchanted worldview of materialistic science, are seeking to relate to the spiritual in nature once again. It is also a major contribution to the holistic science of the plant world, complementing studies by Goethean and anthroposophically inspired researchers into the formative forces at work in the plant kingdom … Anyone who gives proper attention to [this book] will feel that they are indeed brought closer to the mysterious form-creating life-processes that emanate from the world of spirit, and for this reason it is an enormously valuable contribution to all who are endeavouring to work towards a more holistic and spiritual awareness of the plant world.'-- Jeremy Naydler, New View'Keith Critchlow has created a masterpiece, which speaks not only through his inspired and informative text, but also through 560 color [sic] illustrations combining his superb flower photography with hand-drawn geometric patterns. The result is a celebration of the geometric lawfulness of flower forms that embody universal spiritual archetypes … The Hidden Geometry of Flowers is absolutely a must-read book for anyone who wants to be inspired by and appreciate the cosmic forces and archetypes that bestow the qualities we so cherish in each flower, and in their extraordinary healing qualities as flower essences.'-- Warren Kenton, Flower Essence Society'This book is a definitive work on the geometry of the relationship between Nature and the Cosmos. Its text and extraordinary set of photographs and diagrams indicate that there is a Divine Plan that governs the physical dimension as well as the hidden universes beyond. Professor Critchlow's masterpiece is the product of a lifelong labour of love and observation, illustrated with many of his personal drawings … As well as being informative and eye-opening, reading this book is refreshing, like a visit to paradise. --- Z'ev ben Simn Halevi, Caduceus'In the quest to reconnect with the natural world, we need go no further than appreciating flowers for the beauty and hidden geometry that they encompass. In his elegantly presented large-format book, Prod. Keith Critchlow includes over 500 breathtaking colour photographs, illustrations and hand drawings to go with his engaging text … Beauty is the language of flowers, and Critchlow helps entice us into their unfolding, spiralling domains to discover a higher realm of contemplation. Beauty really is truth, as this magnificent work shows.'-- Nexus'This remarkable and beautiful book is the culmination of years of research into the nature and geometry of flowers, drawing on the author's extensive understanding of Platonic philosophy as a means of expressing and understanding the Good, the Beautiful and the True … Reading the book is a form of living education which means that you will never respond to (I did not say look at) flowers in quite the same way again. This is highlighted by the Prince of Wales in his foreword, when he talks about the perception of beauty as a resonance with the patterns which we ourselves are made of. The result is a feeling of harmony, the subject of the Prince's own book.'-- David Lorimer, Network Review, Winter 2011'Critchlow takes four different perspectives to explore how flowers connect us to deeper truths: material, social, cultural and inspirational.His thesis is illustrated with striking photos of plants, together with drawings, diagrams and quotes from Eastern and Western writers,classical philosophers and religious teachers … This book reads like the unfurling of a lifetime’s observation, and afterwards you look at the whole world differently, not just the garden.'-- Garden Design Journal'I eagerly awaited the publication of this book, and I have to say that it was a real delight finally to read its inspirational thoughts and also to contemplate the large number of beautiful images and geometrical diagrams it contains … [The book's] analyses open one's eyes to the extraordinary ability of flowers to harness and express geometrical forms and proportions. They open one's eyes, that is to say, to an underlying order and harmony that are intrinsic to the natural world … through contemplating the geometircal analyses in this book, the reader is directed in wonderment towards this vast domain of ordered and ordering forms … The Hidden Geometry of Flowers is a wonderful gift to the gorwing number of people who, dissatisfied with the impoverished and disenchanted world-view of materialistic science, are seeking to relate to the spiritual in nature once again. It is also a major contribution to the holisitic science of the plant world … [it] is an enormously valuable contribution to all who are endeavouring to work towards a more holistic and spiritual awareness of the plant world.'-- Temenos Academy Review'In his summary he contends that “flowers have been so instrumental forming human ideas of paradise.” His notions are supported by a broad range of illustrations that celebrate the great beauty of flowers in a variety of forms.'-- Chicago Botanic Garden website'At over 400 pages, this is a long work, but it is full of superb illustrations, providing instant appeal… it is also a book of substance as far as the writing is concerned… I consider this to be a book which will "grow" on the reader -- to extend the flower analogy -- and it is full of memorable quotes, which the mathematically challenged reader (like me), or the newcomer to the perennial philosophy, can hold on to while waiting for full understanding to emerge.-- Quest: Journal of the Theosophical Society in America

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Book SynopsisThis book introduces students to projective geometry from an analytic perspective, mixing recent results from the past 100 years with the history of the field in one of the most comprehensive surveys of the subject. The subject is taught conceptually, with worked examples and diagrams to aid in understanding.Trade Review'This book provides a lively and lovely perspective on real projective spaces, combining art, history, groups and elegant proofs.' William M. Kantor'This book is a celebration of the projective viewpoint of geometry. It gradually introduces the reader to the subject, and the arguments are presented in a way that highlights the power of projective thinking in geometry. The reader surprisingly discovers not only that Euclidean and related theorems can be realized as derivatives of projective results, but there are also unnoticed connections between results from ancient times. The treatise also contains a large number of exercises and is dotted with worked examples, which help the reader to appreciate and deeply understand the arguments they refer to. In my opinion this is a book that will definitely change the way we look at the Euclidean and projective analytic geometry.' Alessandro Siciliano, Università degli Studi della BasilicataTable of ContentsPreface; Part I. The Real Projective Plane: 1. Fundamental aspects of the real projective plane; 2. Collineations; 3. Polarities and conics; 4. Cross-ratio; 5. The group of the conic; 6. Involution; 7. Affine plane geometry viewed projectively; 8. Euclidean plane geometry viewed projectively; 9. Transformation geometry: Klein's point of view; 10. The power of projective thinking; 11. From perspective to projective; 12. Remarks on the history of projective geometry; Part II. Two Real Projective 3-Space: 13. Fundamental aspects of real projective space; 14. Triangles and tetrahedra; 15. Reguli and quadrics; 16. Line geometry; 17. Projections; 18. A glance at inversive geometry; Part III. Higher Dimensions: 19. Generalising to higher dimensions; 20. The Klein quadric and Veronese surface; Appendix: Group actions; References; Index.

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Book SynopsisA First Course in Ergodic Theory provides readers with an introductory course in Ergodic Theory. This textbook has been developed from the authorsâ own notes on the subject, which they have been teaching since the 1990s. Over the years they have added topics, theorems, examples and explanations from various sources. The result is a book that is easy to teach from and easy to learn from â designed to require only minimal prerequisites.Features Suitable for readers with only a basic knowledge of measure theory, some topology and a very basic knowledge of functional analysis Perfect as the primary textbook for a course in Ergodic Theory Examples are described and are studied in detail when new properties are presented. Trade Review"A First Course in Ergodic Theory by Dajani and Kalle provides not only a crystal clear introduction to the core of ergodic theory, but also goes down paths previously accessible only through the research literature. The book covers ergodic theorems, invariant measures, entropy and the variational principle. But it also covers piecewise monotone interval maps, Perron-Frobenius operators, natural extensions, and the useful lemma of Knopp. Another theme is the theory of conservative nonsingular and infinite measure preserving transformations. All of this is illustrated via numerous examples from (not necessarily regular) continued fractions and other number expansions, the authors’ specialty. Throughout the book, the proofs patiently explain details often ignored. An excellent appendix provides a reference to needed results from topology, measure theory, probability and functional analysis."– E. Arthur (Robbie) Robinson, Jr., Professor of Mathematics at George Washington University and co-author of The Mathematics of Politics"This textbook is a delightful introduction to Ergodic Theory. It starts at a basic level, giving intuitive explanations and motivations, and concludes with more advanced topics such as variational principle and infinite ergodic theory. The style is very crisp, and many of the results are proved. Examples which are primarily taken from number theory run as a red thread through the manuscript. This makes this textbook quite different from other classic textbooks on the subject. It’s very easy to build an advanced UG or a postgraduate lecture course around this material."– Sebastian van Strien, Imperial College LondonTable of ContentsPreface. Author Bios. 1. Measure preservingness and basic examples. 1.1. What is Ergodic Theory. 1.2. Measure Preserving Transformations. 1.3. Basic Examples. 2. Recurrence and Ergodicity. 2.1. Recurrence. 2.2. Ergodicity. 2.3. Examples of Ergodic Transformations. 3. The Pointwise Ergodic Theorem and its consequences. 3.2. Normal Numbers. 3.3. Characterization of Irreducible Markov Chains. 3.4. Mixing. 4. More Ergodic Theorem. The mean Ergodic Theorem. 4.2. The Hurewicz Erogdic Theorem. 5. Measure Preserving Isomorphisms. 5.2. Factor Maps. 5.3. Natural Extensions. 6. The Perron–Frobenius Operator. 6.1. Absolutely Continuous Invariants Measures. 6.2. Exactness. Densities for Piecewise Monotnoe Interval Maps. 7. Invariant Measures for Continuous Transformations. 7.1. Existence. 7.2. Unique Ergodicity and Inform Distributions. 7.3. Some Topological Dynamics. 8. Continued Fractions. 8.1. Basic Properties of Regular Continue Fractions. 8.2. Ergodic Properties of Gauss Map. 8.3. Natural Extension and the Doeblin–Lenstra Conjecture. 8.4. Other Continue Fraction Transformation. 9. Entropy. 9.1. Randomness and Information. 9.2. Definitions and Properties. Calculation of Entropy and Examples. 9.4. The Shannon–McMillan–Breiman Theorem. 9.5. Lochs’ Theorem. 10. The Variational Principle. 10.1 Topological Entropy. 10.2. Main Theorem. 10.3. Measures of Maximal Entropy. 11. Infinite Ergodic Theory. 11.1 Examples of Infinite Measure Dynamical Systems. 11.2. Conservative and Dissipative Part. 11.3. Induced Systems. 11.4. Jump Transformations. 11.5. Ergodic Theorem for Infinite Measure Systems. 12. Appendix. 12.1. Topology. 12.2. Measure Theory. 12.3 Lebesgue Spaces. 12.4. Lebesgue Integration and Convergence Results. 12.5. Hilbert’s Spaces. 12.6. Borel Measures on Compact Metric Spaces. 12.7. Functions of Bounded Variation. Bibliography. Index.

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Book SynopsisThis textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Feature

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Book SynopsisFirst Steps in Space-Time: A Brief Introduction to Special Relativity provides an accessible, authentic, and readable introduction to the theory of special relativity. The academic level of the book builds only on skills that would be covered in a GCSE maths course, such as Pythagoras's theorem, and rearranging equations, and no prior knowledge of relativity (or physics) is assumed. The key benefits of the work are to bridge the gap between popular science books and university textbooks, and make the theory of relativity as broadly accessible as physically possible. The book allows the reader to discover and appreciate that relativity is not an intractable esoteric curiosity, but a beautiful and succinct theory that profoundly shaped the course of history and our interpretation of our day-to-day lives. This book is ideal for readers with an interest in physics and a little working knowledge of maths, who have studied mathematics at about A-level standard: professionals such

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Book SynopsisWritten in a clear and lively tone, Statistics Using IBM SPSS provides a data-centric approach to statistics with integrated SPSS (version 22) commands, ensuring that students gain both a deep conceptual understanding of statistics and practical facility with the leading statistical software package. With one hundred worked examples, the textbook guides students through statistical practice using real data and avoids complicated mathematics. Numerous end-of-chapter exercises allow students to apply and test their understanding of chapter topics, with detailed answers available online. The third edition has been updated throughout and includes a new chapter on research design, new topics (including weighted mean, resampling with the bootstrap, the role of the syntax file in workflow management, and regression to the mean) and new examples and exercises. Student learning is supported by a rich suite of online resources, including answers to end-of-chapter exercises, real data sets, PowerTrade Review'This is the third edition of a very popular and useful text. The focus is on using SPSS in the research process. The chapters have illustrative exercises and meaningful real data problem sets that not only make it convenient for teaching but also provide realistic experiences for students that will stay with them for many years. The book does a very good job presenting the challenge of data analysis and the experience of being a serious researcher looking at important problems; it illustrates how a variety of quantitative methods can be applied to real data to tease out and evaluate the inferences suggested by that data. I strongly recommend this book to instructors of a one- or two-semester introductory statistics course.' Robert W. Lissitz, University of Maryland'This text by Weinberg and Abramowitz is an excellent choice for an undergraduate or introductory graduate course for non-majors. Stressing concepts over computation, it focuses on essential material for students in education and the social sciences. The book reads easily, like a set of well-constructed lectures that begin with simple fundamental concepts. Yet modern and relatively advanced topics, such as uses of the bootstrap, are also treated. Rather than focusing on hand calculations, the book integrates instruction on using SPSS directly into the text. This enables student exploration of actual research data sets, beginning in the first chapters.' James E. Corter, Columbia University'This book covers a broad range of topics in introductory statistics, employing a hands-on, problem-based approach. The latest edition expands an already long list of topics to include bootstrap techniques and experimental design considerations. By providing detailed, worked-through examples based on real data and substantive research questions, the authors guide the student through the data analysis process from beginning to end. However, this is no 'cookbook' - each section builds on the concepts and techniques established previously, and the reader is encouraged to explore the nuances involved in effective statistical analysis. What is particularly unique about the authors' exposition is that it can be read on many levels; this book will serve well as a course textbook or as a handy reference for the applied researcher.' Marc A. Scott, New York UniversityTable of Contents1. Introduction; 2. Examining univariate distributions; 3. Measures of location, spread, and skewness; 4. Re-expressing variables; 5. Exploring relationships between two variables; 6. Simple linear regression; 7. Probability fundamentals; 8. Theoretical probability models; 9. The role of sampling in inferential statistics; 10. Inferences involving the mean of a single population when σ is known; 11. Inferences involving the mean when σ is not known: one- and two-sample designs; 12. Research design: introduction and overview; 13. One-way analysis of variance; 14. Two-way analysis of variance; 15. Correlation and simple regression as inferential techniques; 16. An introduction to multiple regression; 17. Nonparametric methods.

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Book SynopsisThis series has been developed specifically for the Cambridge International AS & A Level Mathematics (9709) syllabus to be examined from 2020. Cambridge International AS & A Level Mathematics: Probability & Statistics 2 matches the corresponding unit of the syllabus, with a clear and logical progression through. It contains materials on topics such as hypothesis testing, Poisson distribution, linear combinations and continuous random variables, and sampling. This coursebook contains a variety of features including recap sections for students to check their prior knowledge, detailed explanations and worked examples, end-of-chapter and cross-topic review exercises and ''Explore'' tasks to encourage deeper thinking around mathematical concepts. Answers to coursebook questions are at the back of the book.Table of Contents1. Hypothesis testing; 2. Poisson distribution; 3. Linear combinations of random variables; Cross-topic revision exercise 1; 4. Continuous random variables; 5. Sampling; 6. Interpretation of sample data; Cross-topic revision exercise 2; Practice paper; Answers; Glossary; Index.

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Book SynopsisPraise for the Fourth Edition The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control.Mathematical Reviews Bridging classical models and modern topics, the Fifth Edition of Time Series Analysis: Forecasting and Control maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the Fifth Edition continues to serve as one of the most influential and prominent works on the subject. Time Series Analysis: Forecasting and Control, Fifth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic Table of ContentsPREFACE TO THE FIFTH EDITION xix PREFACE TO THE FOURTH EDITION xxiii PREFACE TO THE THIRD EDITION xxv 1 Introduction 1 1.1 Five Important Practical Problems 2 1.2 Stochastic and Deterministic Dynamic Mathematical Models 6 1.3 Basic Ideas in Model Building 14 Appendix A1.1 Use of the R Software 17 Exercises 18 PART ONE STOCHASTIC MODELS AND THEIR FORECASTING 19 2 Autocorrelation Function and Spectrum of Stationary Processes 21 2.1 Autocorrelation Properties of Stationary Models 21 2.2 Spectral Properties of Stationary Models 34 Appendix A2.1 Link Between the Sample Spectrum and Autocovariance Function Estimate 43 Exercises 44 3 Linear Stationary Models 47 3.1 General Linear Process 47 3.2 Autoregressive Processes 54 3.3 Moving Average Processes 68 3.4 Mixed Autoregressive--Moving Average Processes 75 Appendix A3.1 Autocovariances Autocovariance Generating Function and Stationarity Conditions for a General Linear Process 82 Appendix A3.2 Recursive Method for Calculating Estimates of Autoregressive Parameters 84 Exercises 86 4 Linear Nonstationary Models 88 4.1 Autoregressive Integrated Moving Average Processes 88 4.2 Three Explicit Forms for the ARIMA Model 97 4.3 Integrated Moving Average Processes 106 Appendix A4.1 Linear Difference Equations 116 Appendix A4.2 IMA(0 1 1) Process with Deterministic Drift 121 Appendix A4.3 ARIMA Processes with Added Noise 122 Exercises 126 5 Forecasting 129 5.1 Minimum Mean Square Error Forecasts and Their Properties 129 5.2 Calculating Forecasts and Probability Limits 135 5.3 Forecast Function and Forecast Weights 139 5.4 Examples of Forecast Functions and Their Updating 144 5.5 Use of State-Space Model Formulation for Exact Forecasting 155 5.6 Summary 162 Appendix A5.1 Correlation Between Forecast Errors 164 Appendix A5.2 Forecast Weights for any Lead Time 166 Appendix A5.3 Forecasting in Terms of the General Integrated Form 168 Exercises 174 PART TWO STOCHASTIC MODEL BUILDING 177 6 Model Identification 179 6.1 Objectives of Identification 179 6.2 Identification Techniques 180 6.3 Initial Estimates for the Parameters 194 6.4 Model Multiplicity 202 Appendix A6.1 Expected Behavior of the Estimated Autocorrelation Function for a Nonstationary Process 206 Exercises 207 7 Parameter Estimation 209 7.1 Study of the Likelihood and Sum-of-Squares Functions 209 7.2 Nonlinear Estimation 226 7.3 Some Estimation Results for Specific Models 236 7.4 Likelihood Function Based on the State-Space Model 242 7.5 Estimation Using Bayes’ Theorem 245 Appendix A7.1 Review of Normal Distribution Theory 251 Appendix A7.2 Review of Linear Least-Squares Theory 256 Appendix A7.3 Exact Likelihood Function for Moving Average and Mixed Processes 259 Appendix A7.4 Exact Likelihood Function for an Autoregressive Process 266 Appendix A7.5 Asymptotic Distribution of Estimators for Autoregressive Models 274 Appendix A7.6 Examples of the Effect of Parameter Estimation Errors on Variances of Forecast Errors and Probability Limits for Forecasts 277 Appendix A7.7 Special Note on Estimation ofMoving Average Parameters 280 Exercises 280 8 Model Diagnostic Checking 284 8.1 Checking the Stochastic Model 284 8.2 Diagnostic Checks Applied to Residuals 287 8.3 Use of Residuals to Modify the Model 301 Exercises 303 9 Analysis of Seasonal Time Series 305 9.1 Parsimonious Models for Seasonal Time Series 305 9.2 Representation of the Airline Data by a Multiplicative (0 1 1) × (0 1 1)12 Model 310 9.3 Some Aspects of More General Seasonal ARIMA Models 325 9.4 Structural Component Models and Deterministic Seasonal Components 331 9.5 Regression Models with Time Series Error Terms 339 Appendix A9.1 Autocovariances for Some Seasonal Models 345 Exercises 349 10 Additional Topics and Extensions 352 10.1 Tests for Unit Roots in ARIMA Models 353 10.2 Conditional Heteroscedastic Models 361 10.3 Nonlinear Time Series Models 377 10.4 Long Memory Time Series Processes 385 Exercises 392 PART THREE TRANSFER FUNCTION AND MULTIVARIATE MODEL BUILDING 395 11 Transfer Function Models 397 11.1 Linear Transfer Function Models 397 11.2 Discrete Dynamic Models Represented by Difference Equations 404 11.3 Relation Between Discrete and Continuous Models 414 Appendix A11.1 Continuous Models with Pulsed Inputs 420 Appendix A11.2 Nonlinear Transfer Functions and Linearization 424 Exercises 426 12 Identification Fitting and Checking of Transfer Function Models 428 12.1 Cross-Correlation Function 429 12.2 Identification of Transfer Function Models 435 12.3 Fitting and Checking Transfer Function Models 446 12.4 Some Examples of Fitting and Checking Transfer Function Models 453 12.5 Forecasting with Transfer FunctionModels Using Leading Indicators 461 12.6 Some Aspects of the Design of Experiments to Estimate Transfer Functions 469Appendix A12.1 Use of Cross-Spectral Analysis for Transfer Function Model Identification 471 Appendix A12.2 Choice of Input to Provide Optimal Parameter Estimates 473 Exercises 477 13 Intervention Analysis Outlier Detection and Missing Values 481 13.1 Intervention Analysis Methods 481 13.2 Outlier Analysis for Time Series 488 13.3 Estimation for ARMA Models with Missing Values 495 Exercises 502 14 Multivariate Time Series Analysis 505 14.1 Stationary Multivariate Time Series 506 14.2 Vector Autoregressive Models 509 14.3 Vector Moving Average Models 524 14.4 Vector Autoregressive--Moving Average Models 527 14.5 Forecasting for Vector Autoregressive--Moving Average Processes 534 14.6 State-Space Form of the VARMA Model 536 14.7 Further Discussion of VARMA Model Specification 539 14.8 Nonstationarity and Cointegration 546 Appendix A14.1 Spectral Characteristics and Linear Filtering Relations for Stationary Multivariate Processes 552 Exercises 554 PART FOUR DESIGN OF DISCRETE CONTROL SCHEMES 559 15 Aspects of Process Control 561 15.1 Process Monitoring and Process Adjustment 562 15.2 Process Adjustment Using Feedback Control 566 15.3 Excessive Adjustment Sometimes Required by MMSE Control 580 15.4 Minimum Cost Control with Fixed Costs of Adjustment and Monitoring 582 15.5 Feedforward Control 588 15.6 Monitoring Values of Parameters of Forecasting and Feedback Adjustment Schemes 599 Appendix A15.1 Feedback Control Schemes Where the Adjustment Variance Is Restricted 600 Appendix A15.2 Choice of the Sampling Interval 609 Exercises 613 PART FIVE CHARTS AND TABLES 617 COLLECTION OF TABLES AND CHARTS 619 COLLECTION OF TIME SERIES USED FOR EXAMPLES IN THE TEXT AND IN EXERCISES 625 REFERENCES 642 INDEX 659

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Book SynopsisUse TRIZ to unlock creative problem solving Are you new to TRIZ and looking for an easy-to-follow guide on how you can use it to enhance your company's creativity, innovation and problem-solving abilities? Look no further! Written in plain English and packed with tons of accessible and easy-to-follow instruction, TRIZ For Dummies shows you how to use this powerful toolkit to discover all the ways of solving a problem, uncover new concepts and identify previously unseen routes for new product development. An international science that relies on the study of patterns in problems and solutions, TRIZ offers a powerful problem-solving and creativity-generating solution for companies looking to promote innovation, especially in the face of having to do more with less. Inside, you'll find out how to successfully apply this problem-solving toolkit to benefit from the experience of the whole worldnot just the spontaneous and occasional creativity of individuals or groups of engineers with an orTrade ReviewThe book is entertaining and engaging, and reading it may be the first step to changing the way you approach problems forever (Professional Engineering, May 2016)Table of ContentsIntroduction 1 About This Book 2 Foolish Assumptions 3 Icons Used in This Book 3 Beyond the Book 4 Where to Go from Here 4 Part I: Getting Started with TRIZ 5 Chapter 1: Going from Zero to TRIZ 7 Getting to Know TRIZ 8 Increasing Ideality 8 Uncovering patterns in human creativity 10 Learning to think in the abstract 11 Connecting conceptual thinking with your knowledge and experience 13 Going beyond your own experience 14 Thinking functionally 15 Starting Your TRIZ Journey 16 Getting a handle on the TRIZ tools 16 Reapplying proven knowledge to deliver innovative new solutions 17 Modelling problems conceptually 19 Supercharging your thinking 20 Mastering TRIZ 22 Putting the tools together in the TRIZ problem‐solving process 22 Innovating with others by sharing solutions 24 Cultivating the motivation for innovation 24 Being humble and looking like a genius 26 Chapter 2: Understanding the Fundamental TRIZ Philosophy 27 Thinking TRIZ 28 Picturing TRIZ’s beginnings 28 Standing on the shoulders of giants – or reinventing the wheel? 29 Understanding the TRIZ Philosophy 30 Learning to think conceptually 30 Reapplying proven knowledge to solve problems 32 Getting everything you want without changing anything 34 Developing confidence 35 Being Systematic and Creative 36 Using TRIZ processes for understanding and solving problems 36 Thinking freely 37 Challenging assumptions 37 Part II: Opening Your TRIZ Toolbox 39 Chapter 3: Solving Contradictions with the 40 Inventive Principles 41 Uncovering and Understanding Unresolved Conflicts 41 Spotting contradictions and seeing how they’re resolved 42 Understanding the two types of contradiction 44 Reapplying other people’s genius solutions 44 Solving Technical Contradictions 46 Improving imperfect solutions with a little help from your friends 48 Using the Contradiction Matrix 48 Getting to Grips with Physical Contradictions 53 Resolving Physical Contradictions 54 Clever Tricks to Outsmart Contradictions: Using the 40 Inventive Principles 56 Applying the 40 Inventive Principles to real problems 56 Digging for buried treasure in the right places 58 Chapter 4: Applying the Trends of Technical Evolution 61 Looking More Closely at the Trends 62 Discovering the 8 Trends 65 Charting future product directions 69 Achieving a system’s ultimate destiny 73 Applying the Trends 74 Listening to the voice of the product 75 Using the Trends to develop a next‐generation system 76 Moving systems forward and knowing when to go back 78 Applying the Trends More Generally 79 Increasing Ideality 79 Transition to the Super‐System 79 Increasing System Coordination 79 S‐Curves 80 Using the Trends to Create Strong Patents 80 Strengthening and ring‐fencing your own patents 80 Leapfrogging competitors’ technology 81 Chapter 5: Improving Ideality by Using Resources 83 Understanding the Ideality Equation: How TRIZ Defines Value 84 Defining benefits 84 Defining costs 86 Defining downsides 86 Putting the Ideality Equation together 87 Understanding the Links Between Benefits, Functions and Solutions 89 Thinking Resourcefully 90 Understanding resources and where to find them 91 Learning how to hunt for resources 92 Getting what you want using what you have 95 Embedding resource thinking into everyday life 96 Chapter 6: Using the TRIZ Effects Database 99 Thinking Innovatively with the Prism of TRIZ 100 Taking out unnecessary detail 100 Reapplying clever solutions in new and exciting ways 102 Making new connections between existing technologies 104 Using the Database of Scientific Effects 105 Learning to look for what you want 105 Applying the Effects Database to solve problems 106 Strategies for analogous searching 109 Inventing with TRIZ 110 Matching needs and systems 110 Uncovering unmet needs 113 Applying existing technologies to create novel inventions 114 Part III: Thinking Like a Genius 117 Chapter 7: Breaking Psychological Inertia with the TRIZ Creativity Tools 119 Recognising Psychological Inertia 120 Appreciating the Benefits of Psychological Inertia 122 Beating Psychological Inertia 124 Why bad solutions are a good idea 124 Using the 13 TRIZ tools for creative thinking 125 Understanding and Solving Problems Using Smart Little People 127 Modelling problems and solutions conceptually 128 Breaking out of practical thinking 129 Bringing wacky ideas back to reality 130 Stretching Your Thinking with Size–Time–Cost 132 Restructuring your view of what’s possible 133 Finding inventive solutions 134 Chapter 8: Thinking in Time and Scale 137 Stretching Your Thinking in Time and Scale 137 Remembering to stretch yourself 140 Considering whether 9 boxes are really enough 141 Thinking big and thinking small 142 Looking at your situation with new eyes 143 Understanding Problems in Time and Scale 144 Recognising the importance of the big picture 145 Mapping causes of problems and hazards 145 Thinking strategically: Predicting future opportunities and threats 145 Finding Novel Solutions in Time and Scale 148 Locating inventive times and places to solve a problem 148 Covering the waterfront by finding all possible solutions 149 Learning to Think in Time and Scale 151 Chapter 9: Living in Utopia (then Coming Back to Reality) 153 Defining the Ideal Outcome 153 Locating your North Star: Setting your problem‐solving direction 154 Outlining benefits as a team 154 Striving for perfection with the Ideal Outcome, Prime Benefit and Ultimate Goal 156 Setting your constraints 158 Considering stakeholders: Don’t be afraid to ask your customers 159 Taking a Step Towards Reality with Ideal Systems 160 Thinking of what you want and then getting it 160 Using 9 Boxes to define your Ideal System 161 Using divergent thinking with Ideal Functions 162 Making Sensible Decisions by Considering All Benefits, Costs and Harms 163 From perfection to reality: Defining the Ideality you want 164 Learning to compare apples and pears 165 Thinking about the unthinkable: Managing risk 166 Chapter 10: Problem Solving and Being Creative with Others 167 Going for What You Really Want 167 Thinking in Extremes 170 Challenging constraints: Real or imagined? 170 Restructuring problems and solutions 173 Thinking crazily (while being practical) 173 Being Persistent in the Face of Failure 175 Improving imperfect solutions 175 Fixing things when something’s gone wrong 177 Knowing when to stop 178 Sharing and Developing Ideas with Other People 178 Recognising why bad solutions are a good idea 179 Seeing the flaws in your own solutions 180 Learning to love other people’s solutions 181 Capturing, sharing and combining solutions 181 Creating a climate for innovation 182 Part IV: Understanding, Defining and Solving Difficult Problems with TRIZ 185 Chapter 11: Applying the TRIZ Problem‐Solving Process 187 Logically and Systematically Solving Problems 187 Trusting the process (and yourself) 188 Making big leaps by taking small steps 189 Developing your own problem‐solving map 189 Climbing the Problem‐Solving Steps 191 Understanding the overall process 191 Sharpening the axe 193 Knowing your needs and scoping the situation 195 Defining your problem correctly 195 Generating Solutions 196 Expecting the unexpected 196 Applying the TRIZ solution tools 197 Ranking and Developing Solutions 198 Developing solutions further 198 Ranking solutions by Ideality 199 Converging by concept 200 Solving Difficult Problems Effectively in a Team 201 Gaining team understanding and consensus 201 Converging and diverging 201 Thinking fast and thinking slow 202 Putting solutions into practice 203 Chapter 12: Getting to Grips with Your Problems with Function Analysis 205 Making Complex Problems Simple 205 Understanding the building blocks of Function Analysis 207 Defining interactions: The good, the bad and the ugly 208 Charting all parts of your system and beyond 210 Building a Function Analysis Diagram 212 Completing a Function Analysis 212 Listing your components and their interactions 212 Drawing a Function Map 213 Listing, prioritising and solving problems 213 Uncovering Conflicts: Putting Contradictions in Context 214 Understanding How Everything Fits Together 215 Using Function Analysis 216 Modelling difficult problems 217 Gaining the confidence required to change things 218 Achieving clarity in complex situations 220 Communicating effectively 220 Chapter 13: Solving Problems using the TRIZ Standard Solutions 223 Defining a Subject–action–Object 223 Categorising Problems 225 Dealing with Harmful Actions 226 Improving Insufficient Actions 228 Measuring and Detecting 228 Applying the Standard Solutions 231 Developing a well‐formulated problem 231 Solving problems outlined in a Function Analysis 232 Generating innovative solutions 233 Tackling a real problem 235 Improving a solution 237 Chapter 14: Trimming for Elegant, Low‐Cost Solutions 241 Making Things Better and Cheaper 241 Improving systems by removing stuff 242 Clever cost‐cutting: Doing more with less 245 Using resources wisely 247 Creating Elegant Solutions 248 Applying the Trimming Rules 248 Following the process and going off‐piste 252 Trimming to Infinity and Beyond 252 Trimming to Create Strong Intellectual Property 254 Getting round someone else’s patent 254 Developing your own patent further 255 Part V: The Part of Tens 257 Chapter 15: Ten Pitfalls to Avoid 259 Thinking TRIZ Doesn’t Apply to You 259 Waiting for the ‘Right’ Problem 260 Starting Too Big 260 Tackling Problems for Which You Can’t Implement Solutions 261 Tackling Problems without Involving the Problem Owner 261 Trying to Solve Problems When You Don’t Understand the Issue or the Technology 262 Trying to Solve Problems When You Lack Crucial Knowledge 262 Working on a Problem That’s Already Been Solved 263 Undertaking TRIZ by Stealth 263 Giving Up Too Soon 264 Chapter 16: Ten Tips for Getting Started with TRIZ 265 Learn It 265 Use It 266 Start Small 266 Attend a Workshop 266 Think and Talk TRIZ 267 Find a Friend 267 Fail Safely 268 Be Bold 268 Fail Better 269 Reflect 269 Part VI: Appendixes 271 Appendix A: The 40 Inventive Principles 273 Inventive Principle 1: Segmentation 273 Inventive Principle 2: Taking Out 274 Inventive Principle 3: Local Quality 274 Inventive Principle 4: Asymmetry 275 Inventive Principle 5: Merging 275 Inventive Principle 6: Multi‐Function 275 Inventive Principle 7: Nested Doll 276 Inventive Principle 8: Counterweight 276 Inventive Principle 9: Prior Counteraction 276 Inventive Principle 10: Prior Action 277 Inventive Principle 11: Cushion in Advance 277 Inventive Principle 12: Equal Potential 277 Inventive Principle 13: The Other Way Round 278 Inventive Principle 14: Spheres and Curves 278 Inventive Principle 15: Dynamism 279 Inventive Principle 16: Partial or Excessive Action 279 Inventive Principle 17: Another Dimension 279 Inventive Principle 18: Mechanical Vibration 280 Inventive Principle 19: Periodic Action 280 Inventive Principle 20: Continuous Useful Action 281 Inventive Principle 21: Rushing Through 281 Inventive Principle 22: Blessing in Disguise 281 Inventive Principle 23: Feedback 282 Inventive Principle 24: Intermediary 282 Inventive Principle 25: Self‐service 283 Inventive Principle 26: Copying 283 Inventive Principle 27: Cheap, Short‐Living Objects 284 Inventive Principle 28: Replace Mechanical System 284 Inventive Principle 29: Pneumatics and Hydraulics 285 Inventive Principle 30: Flexible Membranes and Thin Films 285 Inventive Principle 31: Porous Materials 285 Inventive Principle 32: Colour Change 286 Inventive Principle 33: Uniform Material 286 Inventive Principle 34: Discarding and Recovering 287 Inventive Principle 35: Parameter Change 287 Inventive Principle 36: Phase Changes 288 Inventive Principle 37: Thermal Expansion 289 Inventive Principle 38: Boosted Interactions 289 Inventive Principle 39: Inert Atmosphere 290 Inventive Principle 40: Composite Structures 290 Appendix B: The Contradiction Matrix 291 Appendix C: The 39 Parameters of the Contradiction Matrix 293 Appendix D: The Separation Principles 299 Appendix E: The Oxford TRIZ Standard Solutions 301 Solutions for Dealing with Harms 302 H1 Trim out the harm 302 H2 Block the harm 303 H3 Turn the harm into good 304 H4 Correct the harm 304 Solutions for Improving Insufficiency 305 i1 Add something to the subject or object 305 i2 Evolve the subject and object 306 i.a Improve the action 307 Solutions for Detection and Measurement 308 M1 Indirect methods 309 M2 Add something 309 M3 Enhance measurement with fields 309 M4 Use additives with fields 310 M5 Evolve the measurement system 310 Index 311

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Book SynopsisBasic Math & Pre-Algebra For Dummies, 2nd Edition (9781119293637) was previously published as Basic Math & Pre-Algebra For Dummies, 2nd Edition (9781118791981). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product. Tips for simplifying tricky basic math and pre-algebra operations Whether you''re a student preparing to take algebra or a parent who wants or needs to brush up on basic math, this fun, friendly guide has the tools you need to get in gear. From positive, negative, and whole numbers to fractions, decimals, and percents, you''ll build necessary math skills to tackle more advanced topics, such as imaginary numbers, variables, and algebraic equations. Explanations and practical examples that mirror today''s teaching methods Relevant cultural vernacular and references Standard For Dummiesmaterials thatTable of ContentsIntroduction 1 About This Book 1 Foolish Assumptions 2 Icons Used in This Book 3 Beyond the Book 3 Where to Go from Here 4 Part 1: Getting Started with Basic Math and Pre-algebra 5 Chapter 1: Playing the Numbers Game 7 Inventing Numbers 8 Understanding Number Sequences 8 Evening the odds 9 Counting by threes, fours, fives, and so on 9 Getting square with square numbers 10 Composing yourself with composite numbers 11 Stepping out of the box with prime numbers 12 Multiplying quickly with exponents 13 Looking at the Number Line 14 Adding and subtracting on the number line 14 Getting a handle on nothing, or zero 15 Taking a negative turn: Negative numbers 16 Multiplying the possibilities 17 Dividing things up 17 Discovering the space in between: Fractions 19 Four Important Sets of Numbers 19 Counting on the counting numbers 20 Introducing integers 20 Staying rational 21 Getting real 21 Chapter 2: It’s All in the Fingers: Numbers and Digits 23 Knowing Your Place Value 23 Counting to ten and beyond 24 Telling placeholders from leading zeros 25 Reading long numbers 26 Close Enough for Rock ’n’ Roll: Rounding and Estimating 26 Rounding numbers 26 Estimating value to make problems easier 28 Table of Contents Chapter 3: The Big Four: Addition, Subtraction, Multiplication, and Division 29 Adding Things Up 30 In line: Adding larger numbers in columns 30 Carry on: Dealing with two-digit answers 31 Take It Away: Subtracting 31 Columns and stacks: Subtracting larger numbers 32 Can you spare a ten? Borrowing to subtract 33 Multiplying 35 Signs of the times 36 Memorizing the multiplication table 37 Double digits: Multiplying larger numbers 40 Doing Division Lickety-Split 42 Making short work of long division 42 Getting leftovers: Division with a remainder 45 Part 2: Getting a Handle on Whole Numbers 47 Chapter 4: Putting the Big Four Operations to Work 49 Knowing Properties of the Big Four Operations 50 Inverse operations 50 Commutative operations 51 Associative operations 52 Distribution to lighten the load 53 Doing Big Four Operations with Negative Numbers 53 Addition and subtraction with negative numbers 54 Multiplication and division with negative numbers 56 Understanding Units 57 Adding and subtracting units 57 Multiplying and dividing units 57 Understanding Inequalities 58 Doesn’t equal (≠) 58 Less than (<) and greater than (>) 59 Less than or equal to (≤) and greater than or equal to (≥) 59 Approximately equals (≈) 60 Moving Beyond the Big Four: Exponents, Square Roots, and Absolute Value 60 Understanding exponents 60 Discovering your roots 61 Figuring out absolute value 62 Chapter 5: A Question of Values: Evaluating Arithmetic Expressions 63 Seeking Equality for All: Equations 64 Basic Math & Pre-Algebra For Dummies, 2nd Edition Hey, it’s just an expression 64 Evaluating the situation 65 Putting the Three E’s together 66 Introducing Order of Operations 66 Applying order of operations to Big Four expressions 67 Using order of operations in expressions with exponents 70 Understanding order of precedence in expressions with parentheses 71 Chapter 6: Say What? Turning Words into Numbers 75 Dispelling Two Myths about Word Problems 76 Word problems aren’t always hard 76 Word problems are useful 76 Solving Basic Word Problems 77 Turning word problems into word equations 77 Plugging in numbers for words 80 Solving More-Complex Word Problems 82 When numbers get serious 82 Too much information 83 Putting it all together 85 Chapter 7: Divisibility 87 Knowing the Divisibility Tricks 87 Counting everyone in: Numbers you can divide everything by 88 In the end: Looking at the final digits 88 Add it up: Checking divisibility by adding up digits 90 Ups and downs: Divisibility by 11 91 Identifying Prime and Composite Numbers 92 Chapter 8: Fabulous Factors and Marvelous Multiples 95 Knowing Six Ways to Say the Same Thing 96 Connecting Factors and Multiples 97 Finding Fabulous Factors 97 Deciding when one number is a factor of another 97 Understanding factor pairs 98 Generating a number’s factors 98 Identifying prime factors 100 Finding the greatest common factor (GCF) 105 Making Marvelous Multiples 105 Generating multiples 105 Finding the least common multiple (LCM) 106 Table of Contents Part 3: Parts of the Whole: Fractions, Decimals, and Percents 109 Chapter 9: Fooling with Fractions 111 Slicing a Cake into Fractions 112 Knowing the Fraction Facts of Life 114 Telling the numerator from the denominator 114 Flipping for reciprocals 114 Using ones and zeros 115 Mixing things up 115 Knowing proper from improper 115 Increasing and Reducing Terms of Fractions 116 Increasing the terms of fractions 117 Reducing fractions to lowest terms 118 Converting between Improper Fractions and Mixed Numbers 120 Knowing the parts of a mixed number 121 Converting a mixed number to an improper fraction 121 Converting an improper fraction to a mixed number 122 Understanding Cross-multiplication 122 Making Sense of Ratios and Proportions 123 Chapter 10: Parting Ways: Fractions and the Big Four Operations 125 Multiplying and Dividing Fractions 126 Multiplying numerators and denominators straight across 126 Doing a flip to divide fractions 127 All Together Now: Adding Fractions 129 Finding the sum of fractions with the same denominator 129 Adding fractions with different denominators 130 Taking It Away: Subtracting Fractions 137 Subtracting fractions with the same denominator 137 Subtracting fractions with different denominators 138 Working Properly with Mixed Numbers 140 Multiplying and dividing mixed numbers 141 Adding and subtracting mixed numbers 142 Chapter 11: Dallying with Decimals 149 Understanding Basic Decimal Stuff 150 Counting dollars and decimals 150 Identifying the place value of decimals 152 Knowing the decimal facts of life 153 Basic Math & Pre-Algebra For Dummies, 2nd Edition Performing the Big Four with Decimals 157 Adding decimals 158 Subtracting decimals 159 Multiplying decimals 160 Dividing decimals 161 Converting between Decimals and Fractions 165 Making simple conversions 165 Changing decimals to fractions 165 Changing fractions to decimals 167 Chapter 12: Playing with Percents 171 Making Sense of Percents 171 Dealing with Percents Greater than 100% 172 Converting to and from Percents, Decimals, and Fractions 173 Going from percents to decimals 173 Changing decimals into percents 174 Switching from percents to fractions 174 Turning fractions into percents 175 Solving Percent Problems 175 Figuring out simple percent problems 176 Turning the problem around 177 Deciphering more-difficult percent problems 178 Putting All the Percent Problems Together 178 Identifying the three types of percent problems 179 Solving percent problems with equations 180 Chapter 13: Word Problems with Fractions, Decimals, and Percents 183 Adding and Subtracting Parts of the Whole in Word Problems 184 Sharing a pizza: Fractions 184 Buying by the pound: Decimals 185 Splitting the vote: Percents 185 Problems about Multiplying Fractions 186 Renegade grocery shopping: Buying less than they tell you to 186 Easy as pie: Working out what’s left on your plate 187 Multiplying Decimals and Percents in Word Problems 188 To the end: Figuring out how much money is left 188 Finding out how much you started with 189 Handling Percent Increases and Decreases in Word Problems 191 Raking in the dough: Finding salary increases 191 Earning interest on top of interest 192 Getting a deal: Calculating discounts 193 Table of Contents Part 4: Picturing and Measuring — Graphs, Measures, Stats, and Sets 195 Chapter 14: A Perfect Ten: Condensing Numbers with Scientific Notation 197 First Things First: Using Powers of Ten as Exponents 198 Counting zeros and writing exponents 198 Adding exponents to multiply 200 Working with Scientific Notation 200 Writing in scientific notation 201 Seeing why scientific notation works 202 Understanding order of magnitude 203 Multiplying with scientific notation 203 Chapter 15: How Much Have You Got? Weights and Measures 205 Examining Differences between the English and Metric Systems 206 Looking at the English system 206 Looking at the metric system 208 Estimating and Converting between the English and Metric Systems 210 Estimating in the metric system 211 Converting units of measurement 213 Chapter 16: Picture This: Basic Geometry 217 Getting on the Plane: Points, Lines, Angles, and Shapes 218 Making some points 218 Knowing your lines 218 Figuring the angles 219 Shaping things up 221 Closed Encounters: Shaping Up Your Understanding of 2-D Shapes 221 Polygons 222 Circles 224 Taking a Trip to Another Dimension: Solid Geometry 225 The many faces of polyhedrons 225 3-D shapes with curves 226 Measuring Shapes: Perimeter, Area, Surface Area, and Volume 227 2-D: Measuring on the flat 228 Spacing out: Measuring in three dimensions 235 Basic Math & Pre-Algebra For Dummies, 2nd Edition Chapter 17: Seeing Is Believing: Graphing as a Visual Tool 239 Looking at Three Important Graph Styles 240 Bar graph 240 Pie chart 241 Line graph 242 Using the xy-Graph 243 Plotting points on an xy-graph 244 Drawing lines on an xy-graph 245 Chapter 18: Solving Geometry and Measurement Word Problems 247 The Chain Gang: Solving Measurement Problems with Conversion Chains 248 Setting up a short chain 248 Working with more links 249 Pulling equations out of the text 250 Rounding off: Going for the short answer 251 Solving Geometry Word Problems 253 Working from words and images 253 Breaking out those sketching skills 255 Chapter 19: Figuring Your Chances: Statistics and Probability 259 Gathering Data Mathematically: Basic Statistics 260 Understanding differences between qualitative and quantitative data 260 Working with qualitative data 261 Working with quantitative data 264 Looking at Likelihoods: Basic Probability 266 Figuring the probability 267 Oh, the possibilities! Counting outcomes with multiple coins 268 Chapter 20: Setting Things Up with Basic Set Theory 271 Understanding Sets 272 Elementary, my dear: Considering what’s inside sets 273 Sets of numbers 275 Performing Operations on Sets 275 Union: Combined elements 276 Intersection: Elements in common 276 Relative complement: Subtraction (sorta) 277 Complement: Feeling left out 277 Table of Contents Part 5: the X-files: Introduction to Algebra 279 Chapter 21: Enter Mr X: Algebra and Algebraic Expressions 281 Seeing How X Marks the Spot 282 Expressing Yourself with Algebraic Expressions 282 Evaluating algebraic expressions 283 Coming to algebraic terms 285 Making the commute: Rearranging your terms 286 Identifying the coefficient and variable 287 Identifying like terms 288 Considering algebraic terms and the Big Four 289 Simplifying Algebraic Expressions 292 Combining like terms 292 Removing parentheses from an algebraic expression 293 Chapter 22: Unmasking Mr X: Algebraic Equations 299 Understanding Algebraic Equations 300 Using X in Equations 300 Choosing among four ways to solve algebraic equations 301 The Balancing Act: Solving for x 302 Striking a balance 303 Using the Balance Scale to Isolate X 304 Rearranging Equations and Isolating x 305 Rearranging terms on one side of an equation 305 Moving terms to the other side of the equals sign 306 Removing parentheses from equations 307 Cross-multiplying 309 Chapter 23: Putting Mr X to Work: Algebra Word Problems 311 Solving Algebra Word Problems in Five Steps 312 Declaring a variable 312 Setting up the equation 313 Solving the equation 314 Answering the question 314 Checking your work 315 Choosing Your Variable Wisely 315 Solving More-Complex Algebraic Problems 316 Charting four people 316 Crossing the finish line with five people 318 Basic Math & Pre-Algebra For Dummies, 2nd Edition Part 6: the Part of Tens 321 Chapter 24: Ten Little Math Demons That Trip People Up 323 Knowing the Multiplication Table 324 Adding and Subtracting Negative Numbers 324 Multiplying and Dividing Negative Numbers 325 Knowing the Difference between Factors and Multiples 325 Reducing Fractions to Lowest Terms 326 Adding and Subtracting Fractions 326 Multiplying and Dividing Fractions 327 Identifying Algebra’s Main Goal: Find X 327 Knowing Algebra’s Main Rule: Keep the Equation in Balance 328 Seeing Algebra’s Main Strategy: Isolate x 328 Chapter 25: Ten Important Number Sets to Know 329 Counting on Counting (or Natural) Numbers 330 Identifying Integers 330 Knowing the Rationale behind Rational Numbers 331 Making Sense of Irrational Numbers 331 Absorbing Algebraic Numbers 332 Moving through Transcendental Numbers 333 Getting Grounded in Real Numbers 333 Trying to Imagine Imaginary Numbers 333 Grasping the Complexity of Complex Numbers 334 Going beyond the Infinite with Transfinite Numbers 335 Index 337

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Book SynopsisHarness the seven key elements of successful organisational change Leading for Organisational Change is an intelligent and practical guide to the human side of merger integration and other organisational change. Building a clear sense of common purpose and then reinforcing it through storytelling can underpin the success of an integration or significant change programme. Pulling together the best thinking from neuroscience, psychology and business, and her rich personal experience in twenty years of leading change projects in professional services organisations and other people-centred businesses, author Jennifer Emery presents a framework for change rooted in seven key themes that help organisations establish their BECAUSE: belonging, evolution, confidence, agility, understanding, simplicity and energy. Exploring the role each theme plays in the context of change, this insightful and warm book shares real-world examples and provides advice on building purpose aTable of ContentsIntroduction 1 Part One: Foundation 13 1 Once Upon a Time 15 2 The Angel in the Marble 21 3 Milk and Mushrooms 33 4 Telling Stories 39 5 Everything Must Change 45 Part Two: Story 59 6 Beginnings 61 7 Starting Out 77 8 Making It Happen 97 Part Three: Because 119 9 Belonging 121 10 Evolution 141 11 Confidence 159 12 Agility 179 13 Understanding 201 14 Simplicity 223 15 Energy 245 Part Four: Implications 265 16 The Bigger Picture 267 17 The Best Thing You Can Bring is Heart 279 Bibliography 289 Acknowledgements 297 About the Author 299 Index 301

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Book SynopsisTable of ContentsIntroduction 1 About This Book 1 Foolish Assumptions 3 Icons Used in This Book 4 Beyond the Book 4 Where to Go from Here 5 Book 1: Defining Data Science 7 Chapter 1: Considering the History and Uses of Data Science 9 Considering the Elements of Data Science 10 Considering the emergence of data science 10 Outlining the core competencies of a data scientist 11 Linking data science, big data, and AI 12 Understanding the role of programming 12 Defining the Role of Data in the World 13 Enticing people to buy products 13 Keeping people safer 14 Creating new technologies 15 Performing analysis for research 16 Providing art and entertainment 17 Making life more interesting in other ways 18 Creating the Data Science Pipeline 18 Preparing the data 18 Performing exploratory data analysis 18 Learning from data 19 Visualizing 19 Obtaining insights and data products 19 Comparing Different Languages Used for Data Science 20 Obtaining an overview of data science languages 20 Defining the pros and cons of using Python 22 Defining the pros and cons of using R 23 Learning to Perform Data Science Tasks Fast 25 Loading data 26 Training a model 26 Viewing a result 26 Chapter 2: Placing Data Science within the Realm of AI 29 Seeing the Data to Data Science Relationship 30 Considering the data architecture 30 Acquiring data from various sources 31 Performing data analysis 32 Archiving the data 33 Defining the Levels of AI 33 Beginning with AI 34 Advancing to machine learning 39 Getting detailed with deep learning 43 Creating a Pipeline from Data to AI 47 Considering the desired output 47 Defining a data architecture 47 Combining various data sources 47 Checking for errors and fixing them 48 Performing the analysis 48 Validating the result 49 Enhancing application performance 49 Chapter 3: Creating a Data Science Lab of Your Own 51 Considering the Analysis Platform Options 52 Using a desktop system 53 Working with an online IDE 53 Considering the need for a GPU 54 Choosing a Development Language 56 Obtaining and Using Python 58 Working with Python in this book 58 Obtaining and installing Anaconda for Python 59 Defining a Python code repository 64 Working with Python using Google Colaboratory 69 Defining the limits of using Azure Notebooks with Python and R 71 Obtaining and Using R 72 Obtaining and installing Anaconda for R 72 Starting the R environment 73 Defining an R code repository 75 Presenting Frameworks 76 Defining the differences 76 Explaining the popularity of frameworks 77 Choosing a particular library 79 Accessing the Downloadable Code 80 Chapter 4: Considering Additional Packages and Libraries You Might Want 81 Considering the Uses for Third-Party Code 82 Obtaining Useful Python Packages 83 Accessing scientific tools using SciPy 84 Performing fundamental scientific computing using NumPy 85 Performing data analysis using pandas 85 Implementing machine learning using Scikit-learn 86 Going for deep learning with Keras and TensorFlow 86 Plotting the data using matplotlib 87 Creating graphs with NetworkX 88 Parsing HTML documents using Beautiful Soup 88 Locating Useful R Libraries 89 Using your Python code in R with reticulate 89 Conducting advanced training using caret 90 Performing machine learning tasks using mlr 90 Visualizing data using ggplot2 91 Enhancing ggplot2 using esquisse 91 Creating graphs with igraph 91 Parsing HTML documents using rvest 92 Wrangling dates using lubridate 92 Making big data simpler using dplyr and purrr 93 Chapter 5: Leveraging a Deep Learning Framework 95 Understanding Deep Learning Framework Usage 96 Working with Low-End Frameworks 97 Chainer 97 PyTorch 98 MXNet 98 Microsoft Cognitive Toolkit/CNTK 99 Understanding TensorFlow 100 Grasping why TensorFlow is so good 101 Making TensorFlow easier by using TFLearn 102 Using Keras as the best simplifier 102 Getting your copy of TensorFlow and Keras 103 Fixing the C++ build tools error in Windows 106 Accessing your new environment in Notebook 108 Book 2: Interacting with Data Storage 109 Chapter 1: Manipulating Raw Data 111 Defining the Data Sources 112 Obtaining data locally 112 Using online data sources 117 Employing dynamic data sources 121 Considering other kinds of data sources 123 Considering the Data Forms 124 Working with pure text 124 Accessing formatted text 125 Deciphering binary data 126 Understanding the Need for Data Reliability 128 Chapter 2: Using Functional Programming Techniques 131 Defining Functional Programming 132 Differences with other programming paradigms 132 Understanding its goals 133 Understanding Pure and Impure Languages 134 Using the pure approach 134 Using the impure approach 134 Comparing the Functional Paradigm 135 Imperative 135 Procedural 136 Object-oriented 136 Declarative 136 Using Python for Functional Programming Needs 137 Understanding How Functional Data Works 138 Working with immutable data 139 Considering the role of state 139 Eliminating side effects 140 Passing by reference versus by value 140 Working with Lists and Strings 142 Creating lists 144 Evaluating lists 144 Performing common list manipulations 146 Understanding the Dict and Set alternatives 147 Considering the use of strings 148 Employing Pattern Matching 150 Looking for patterns in data 150 Understanding regular expressions 152 Using pattern matching in analysis 155 Working with pattern matching 156 Working with Recursion 159 Performing tasks more than once 159 Understanding recursion 161 Using recursion on lists 162 Considering advanced recursive tasks 163 Passing functions instead of variables 164 Performing Functional Data Manipulation 165 Slicing and dicing 166 Mapping your data 167 Filtering data 168 Organizing data 169 Chapter 3: Working with Scalars, Vectors, and Matrices 171 Considering the Data Forms 172 Defining Data Type through Scalars 173 Creating Organized Data with Vectors 174 Defining a vector 175 Creating vectors of a specific type 175 Performing math on vectors 176 Performing logical and comparison tasks on vectors 176 Multiplying vectors 177 Creating and Using Matrices 178 Creating a matrix 178 Creating matrices of a specific type 179 Using the matrix class 181 Performing matrix multiplication 181 Executing advanced matrix operations 183 Extending Analysis to Tensors 185 Using Vectorization Effectively 186 Selecting and Shaping Data 187 Slicing rows 188 Slicing columns 188 Dicing 189 Concatenating 189 Aggregating 194 Working with Trees 195 Understanding the basics of trees 195 Building a tree 196 Representing Relations in a Graph 198 Going beyond trees 198 Arranging graphs 199 Chapter 4: Accessing Data in Files 201 Understanding Flat File Data Sources 202 Working with Positional Data Files 203 Accessing Data in CSV Files 205 Working with a simple CSV file 205 Making use of header information 208 Moving On to XML Files 209 Working with a simple XML file 209 Parsing XML 211 Using XPath for data extraction 212 Considering Other Flat-File Data Sources 214 Working with Nontext Data 215 Downloading Online Datasets 218 Working with package datasets 218 Using public domain datasets 219 Chapter 5: Working with a Relational DBMS 223 Considering RDBMS Issues 224 Defining the use of tables 225 Understanding keys and indexes 226 Using local versus online databases 227 Working in read-only mode 228 Accessing the RDBMS Data 228 Using the SQL language 229 Relying on scripts 231 Relying on views 231 Relying on functions 232 Creating a Dataset 233 Combining data from multiple tables 233 Ensuring data completeness 234 Slicing and dicing the data as needed 234 Mixing RDBMS Products 234 Chapter 6: Working with a NoSQL DMBS 237 Considering the Ramifications of Hierarchical Data 238 Understanding hierarchical organization 238 Developing strategies for freeform data 239 Performing an analysis 240 Working around dangling data 241 Accessing the Data 243 Creating a picture of the data form 243 Employing the correct transiting strategy 244 Ordering the data 247 Interacting with Data from NoSQL Databases 248 Working with Dictionaries 249 Developing Datasets from Hierarchical Data 250 Processing Hierarchical Data into Other Forms 251 Book 3: Manipulating Data Using Basic Algorithms 253 Chapter 1: Working with Linear Regression 255 Considering the History of Linear Regression 256 Combining Variables 257 Working through simple linear regression 257 Advancing to multiple linear regression 260 Considering which question to ask 262 Reducing independent variable complexity 263 Manipulating Categorical Variables 265 Creating categorical variables 266 Renaming levels 267 Combining levels 268 Using Linear Regression to Guess Numbers 269 Defining the family of linear models 270 Using more variables in a larger dataset 271 Understanding variable transformations 274 Doing variable transformations 275 Creating interactions between variables 277 Understanding limitations and problems 282 Learning One Example at a Time 283 Using Gradient Descent 283 Implementing Stochastic Gradient Descent 283 Considering the effects of regularization 287 Chapter 2: Moving Forward with Logistic Regression 289 Considering the History of Logistic Regression 290 Differentiating between Linear and Logistic Regression 291 Considering the model 291 Defining the logistic function 292 Understanding the problems that logistic regression solves 294 Fitting the curve 295 Considering a pass/fail example 296 Using Logistic Regression to Guess Classes 297 Applying logistic regression 297 Considering when classes are more 298 Defining logistic regression performance 300 Switching to Probabilities 301 Specifying a binary response 301 Transforming numeric estimates into probabilities 302 Working through Multiclass Regression 305 Understanding multiclass regression 305 Developing a multiclass regression implementation 306 Chapter 3: Predicting Outcomes Using Bayes 309 Understanding Bayes’ Theorem 310 Delving into Bayes history 310 Considering the basic theorem 312 Using Naïve Bayes for Predictions 313 Finding out that Naïve Bayes isn’t so naïve 314 Predicting text classifications 315 Getting an overview of Bayesian inference 318 Working with Networked Bayes 324 Considering the network types and uses 324 Understanding Directed Acyclic Graphs (DAGs) 327 Employing networked Bayes in predictions 328 Deciding between automated and guided learning 332 Considering the Use of Bayesian Linear Regression 332 Considering the Use of Bayesian Logistic Regression 333 Chapter 4: Learning with K-Nearest Neighbors 335 Considering the History of K-Nearest Neighbors 336 Learning Lazily with K-Nearest Neighbors 337 Understanding the basis of KNN 337 Predicting after observing neighbors 338 Choosing the k parameter wisely 341 Leveraging the Correct k Parameter 342 Understanding the k parameter 342 Experimenting with a flexible algorithm 343 Implementing KNN Regression 345 Implementing KNN Classification 347 Book 4: Performing Advanced Data Manipulation 351 Chapter 1: Leveraging Ensembles of Learners 353 Leveraging Decision Trees 354 Growing a forest of trees 356 Seeing Random Forests in action 358 Understanding the importance measures 360 Configuring your system for importance measures with Python 361 Seeing importance measures in action 361 Working with Almost Random Guesses 364 Understanding the premise 365 Bagging predictors with AdaBoost 366 Meeting Again with Gradient Descent 369 Understanding the GBM difference 369 Seeing GBM in action 371 Averaging Different Predictors 372 Chapter 2: Building Deep Learning Models 373 Discovering the Incredible Perceptron 374 Understanding perceptron functionality 375 Touching the nonseparability limit 376 Hitting Complexity with Neural Networks 378 Considering the neuron 379 Pushing data with feed-forward 381 Defining hidden layers 383 Executing operations 384 Considering the details of data movement through the neural network 386 Using backpropagation to adjust learning 387 Understanding More about Neural Networks 390 Getting an overview of the neural network process 391 Defining the basic architecture 391 Documenting the essential modules 393 Solving a simple problem 396 Looking Under the Hood of Neural Networks 399 Choosing the right activation function 399 Relying on a smart optimizer 401 Setting a working learning rate 402 Explaining Deep Learning Differences with Other Forms of AI 402 Adding more layers 403 Changing the activations 405 Adding regularization by dropout 406 Using online learning 407 Transferring learning 407 Learning end to end 408 Chapter 3: Recognizing Images with CNNs 409 Beginning with Simple Image Recognition 410 Considering the ramifications of sight 410 Working with a set of images 411 Extracting visual features 417 Recognizing faces using Eigenfaces 419 Classifying images 423 Understanding CNN Image Basics 427 Moving to CNNs with Character Recognition 429 Accessing the dataset 430 Reshaping the dataset 431 Encoding the categories 432 Defining the model 432 Using the model 433 Explaining How Convolutions Work 435 Understanding convolutions 435 Simplifying the use of pooling 439 Describing the LeNet architecture 440 Detecting Edges and Shapes from Images 446 Visualizing convolutions 447 Unveiling successful architectures 449 Discussing transfer learning 450 Chapter 4: Processing Text and Other Sequences 453 Introducing Natural Language Processing 454 Defining the human perspective as it relates to data science 454 Considering the computer perspective as it relates to data science 455 Understanding How Machines Read 456 Creating a corpus 457 Performing feature extraction 457 Understanding the BoW 458 Processing and enhancing text 459 Maintaining order using n-grams 461 Stemming and removing stop words 462 Scraping textual datasets from the web 465 Handling problems with raw text 470 Storing processed text data in sparse matrices 473 Understanding Semantics Using Word Embeddings 478 Using Scoring and Classification 482 Performing classification tasks 482 Analyzing reviews from e-commerce 485 Book 5: Performing Data-Related Tasks 491 Chapter 1: Making Recommendations 493 Realizing the Recommendation Revolution 494 Downloading Rating Data 495 Navigating through anonymous web data 496 Encountering the limits of rating data 499 Leveraging SVD 506 Considering the origins of SVD 506 Understanding the SVD connection 508 Chapter 2: Performing Complex Classifications 509 Using Image Classification Challenges 510 Delving into ImageNet and Coco 511 Learning the magic of data augmentation 513 Distinguishing Traffic Signs 516 Preparing the image data 517 Running a classification task 520 Chapter 3: Identifying Objects 525 Distinguishing Classification Tasks 526 Understanding the problem 526 Performing localization 527 Classifying multiple objects 528 Annotating multiple objects in images 529 Segmenting images 530 Perceiving Objects in Their Surroundings 531 Considering vision needs in self-driving cars 531 Discovering how RetinaNet works 532 Using the Keras-RetinaNet code 534 Overcoming Adversarial Attacks on Deep Learning Applications 538 Tricking pixels 539 Hacking with stickers and other artifacts 541 Chapter 4: Analyzing Music and Video 543 Learning to Imitate Art and Life 544 Transferring an artistic style 545 Reducing the problem to statistics 546 Understanding that deep learning doesn’t create 548 Mimicking an Artist 548 Defining a new piece based on a single artist 549 Combining styles to create new art 550 Visualizing how neural networks dream 551 Using a network to compose music 551 Other creative avenues 552 Moving toward GANs 553 Finding the key in the competition 554 Considering a growing field 556 Chapter 5: Considering Other Task Types 559 Processing Language in Texts 560 Considering the processing methodologies 560 Defining understanding as tokenization 561 Putting all the documents into a bag 562 Using AI for sentiment analysis 566 Processing Time Series 574 Defining sequences of events 574 Performing a prediction using LSTM 575 Chapter 6: Developing Impressive Charts and Plots 579 Starting a Graph, Chart, or Plot 580 Understanding the differences between graphs, charts, and plots 580 Considering the graph, chart, and plot types 582 Defining the plot 583 Drawing multiple lines 584 Drawing multiple plots 584 Saving your work 586 Setting the Axis, Ticks, and Grids 587 Getting the axis 587 Formatting the ticks 590 Adding grids 590 Defining the Line Appearance 591 Working with line styles 592 Adding markers 593 Using Labels, Annotations, and Legends 594 Adding labels 595 Annotating the chart 596 Creating a legend 598 Creating Scatterplots 599 Depicting groups 599 Showing correlations 600 Plotting Time Series 603 Representing time on axes 604 Plotting trends over time 605 Plotting Geographical Data 608 Getting the toolkit 608 Drawing the map 609 Plotting the data 613 Visualizing Graphs 615 Understanding the adjacency matrix 615 Using NetworkX basics 615 Book 6: Diagnosing and Fixing Errors 619 Chapter 1: Locating Errors in Your Data 621 Considering the Types of Data Errors 622 Obtaining the Required Data 624 Considering the data sources 624 Obtaining reliable data 625 Making human input more reliable 626 Using automated data collection 628 Validating Your Data 629 Figuring out what’s in your data 629 Removing duplicates 631 Creating a data map and a data plan 632 Manicuring the Data 634 Dealing with missing data 634 Considering data misalignments 639 Separating out useful data 640 Dealing with Dates in Your Data 640 Formatting date and time values 641 Using the right time transformation 641 Chapter 2: Considering Outrageous Outcomes 643 Deciding What Outrageous Means 644 Considering the Five Mistruths in Data 645 Commission 645 Omission 646 Perspective 646 Bias 647 Frame-of-reference 648 Considering Detection of Outliers 649 Understanding outlier basics 649 Finding more things that can go wrong 651 Understanding anomalies and novel data 651 Examining a Simple Univariate Method 653 Using the pandas package 653 Leveraging the Gaussian distribution 655 Making assumptions and checking out 656 Developing a Multivariate Approach 657 Using principle component analysis 658 Using cluster analysis 659 Automating outliers detection with Isolation Forests 661 Chapter 3: Dealing with Model Overfitting and Underfitting 663 Understanding the Causes 664 Considering the problem 664 Looking at underfitting 665 Looking at overfitting 666 Plotting learning curves for insights 668 Determining the Sources of Overfitting and Underfitting 670 Understanding bias and variance 671 Having insufficient data 671 Being fooled by data leakage 672 Guessing the Right Features 672 Selecting variables like a pro 673 Using nonlinear transformations 676 Regularizing linear models 684 Chapter 4: Obtaining the Correct Output Presentation 689 Considering the Meaning of Correct 690 Determining a Presentation Type 691 Considering the audience 691 Defining a depth of detail 692 Ensuring that the data is consistent with audience needs 693 Understanding timeliness 693 Choosing the Right Graph 694 Telling a story with your graphs 694 Showing parts of a whole with pie charts 694 Creating comparisons with bar charts 695 Showing distributions using histograms 697 Depicting groups using boxplots 699 Defining a data flow using line graphs 700 Seeing data patterns using scatterplots 701 Working with External Data 702 Embedding plots and other images 703 Loading examples from online sites 703 Obtaining online graphics and multimedia 704 Chapter 5: Developing Consistent Strategies 707 Standardizing Data Collection Techniques 707 Using Reliable Sources 709 Verifying Dynamic Data Sources 711 Considering the problem 712 Analyzing streams with the right recipe 714 Looking for New Data Collection Trends 715 Weeding Old Data 716 Considering the Need for Randomness 717 Considering why randomization is needed 718 Understanding how probability works 718 Index 721

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Book SynopsisMake calculus more manageable with simplified instruction and tons of practice Calculus All-in-One For Dummies pairs no-nonsense explanations of calculus content with practical examples and practice problems, so you can untangle the difficult concepts and improve your score in any calculus class. Plus, this book comes with access to chapter quizzes online. Dummies makes differentiation, integration, and everything in between more manageable, so you can crush calculus with confidence. Review the foundational basics, then dive into calc lessons that track your class. This book takes you through a full year of high-school calculus or a first semester of college calculus, only explained more clearly. Work through easy-to-understand lessons on everything in a typical calc classGet the score you want and need on standardized tests like AP CalculusAccess online chapter quizzes for additional practiceUntangle tricky problems and discover clever ways to solve themWith clear definitions, concise explanations, and plenty of helpful information on everything from limits and vectors to integration and curve-sketching, Calculus All-in-One For Dummies is the must-have resource for students who want to review for exams or just need extra help understanding the concepts from class.Table of ContentsIntroduction 1 Unit 1: An Overview of Calculus 5 Chapter 1: What Is Calculus? 7 Chapter 2: The Two Big Ideas of Calculus: Differentiation and Integration — Plus Infinite Series 13 Chapter 3: Why Calculus Works 21 Unit 2: Warming Up with Calculus Prerequisites 25 Chapter 4: Pre-Algebra, Algebra, and Geometry Review 27 Chapter 5: Funky Functions and Their Groovy Graphs 67 Chapter 6: The Trig Tango 95 Unit 3: Limits 117 Chapter 7: Limits and Continuity 119 Chapter 8: Evaluating Limits 141 Unit 4: Differentiation 181 Chapter 9: Differentiation Orientation 183 Chapter 10: Differentiation Rules — Yeah, Man, It Rules 215 Chapter 11: Differentiation and the Shape of Curves 259 Chapter 12: Your Problems Are Solved: Differentiation to the Rescue! 321 Chapter 13: More Differentiation Problems: Going Off on a Tangent 367 Unit 5: Integration and Infinite Series 397 Chapter 14: Intro to Integration and Approximating Area 399 Chapter 15: Integration: It’s Backwards Differentiation 439 Chapter 16: Integration Techniques for Experts 479 Chapter 17: Who Needs Freud? Using the Integral to Solve Your Problems 521 Chapter 18: Taming the Infinite with Improper Integrals 557 Chapter 19: Infinite Series: Welcome to the Outer Limits 581 Index 623

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Book SynopsisDo you want to use R to tell stories? This book was written for youwhether you already know some R or have never coded before.Most R texts focus only on programming or statistical theory. Practical R for Mass Communication and Journalism gives you ideas, tools, and techniques for incorporating data and visualizations into your narratives.You'll see step by step how to: Analyze airport flight delays, restaurant inspections, and election results Map bank locations, median incomes, and new voting districts Compare campaign contributions to final election results Extract data from PDFs Whip messy data into shape for analysis Scrape data from a website Create graphics ranging from simple, static charts to interactive visualizations for the Web If you work or plan to work in a neTrade Review"Practical R for Mass Communication and Journalism looks to me like a fabulous resource for those folks who always wanted to learn some more R but were afraid to ask. Definitely recommended." ~Carl Howe, Director of Education, RStudio"The book can provide a good starting point into working with R. It covers a lot of perspectives that are expected in newsrooms all over the world, especially working with geospatial data. It also provides a lot of good examples and interesting additional resources. The packages used are also mainly part of the standard corpus of R-packages." ~Benedict Witzenberger, Süddeutsche Zeitung"I am the data editor of a mid-sized newsroom. I have long wished for an Intro to R book that was geared toward journalists, not data scientists. I’ve found that fellow journalists are much more likely to pick up on the intricacies of a computing language like R when they encounter it through a relatable example, like visualizing Election Night votes or analyzing a city council budget. Additionally, there are some R functions that simply aren’t useful for the quantitative needs of most journalists. This is what I appreciated the most about the book – its practical nature (the title doesn’t lie!) Machlis focuses on the concepts that data journalists most frequently encounter and spends little to no time on those they don’t…I also appreciated Chapter 17, "An R Project from Start to Finish." This chapter is exactly why I’ve wanted a journalism-specific Intro to R project that I can recommend to my colleagues" ~Ryann Jones, Deputy Editor, Data at ProPublica"I like the book. It’s conversationally written, it walks you through common problems in data journalism and for the most part uses the most common libraries to analyze and visualize data…The book’s instructional approach is the real value – it seems aimed at an audience that needs a narrative in order to understand code and analysis. Conveniently, that pretty well describes journalism students and working professionals…I would recommend publication. It advances the field of data journalism and presents a solid text for instructors or practitioners who are interested in R for analysis." ~Matthew Waite"I NEED THIS BOOK. I may adopt it as a textbook." ~Alberto Cairo, University of Miami"I’m reading this book now and it is terrific. Highly recommended for anyone interested in learning R. I will be using this book in my Data Analysis for Journalists class in the spring." ~Rob Wells, University of Arkansas"Sharon Machlis' 'Practical R for Mass Communication and Journalism' is based on the author's workshops for journalists. This book dives straight into doing the kinds of things a busy reporter or news analyst needs to do to meet a 5:00 pm deadline: data cleaning, presentation-quality graphics, and maps take precedence over control flow or the niceties of variable scope. I particularly enjoyed the way each chapter starts with a realistic project and works through what's needed to build it. People who've never programmed before will be a little intimidated by how many packages they need to download if they try to work through the material on their own, but the instructions are clear, and the author's enthusiasm for her material shines through in every example." ~Greg Wilson, RStudio"Practical R for Mass Communication and Journalism looks to me like a fabulous resource for those folks who always wanted to learn some more R but were afraid to ask. Definitely recommended." ~Carl Howe, Director of Education, RStudio"The book can provide a good starting point into working with R. It covers a lot of perspectives that are expected in newsrooms all over the world, especially working with geospatial data. It also provides a lot of good examples and interesting additional resources. The packages used are also mainly part of the standard corpus of R-packages." ~Benedict Witzenberger, Süddeutsche Zeitung"I am the data editor of a mid-sized newsroom. I have long wished for an Intro to R book that was geared toward journalists, not data scientists. I’ve found that fellow journalists are much more likely to pick up on the intricacies of a computing language like R when they encounter it through a relatable example, like visualizing Election Night votes or analyzing a city council budget. Additionally, there are some R functions that simply aren’t useful for the quantitative needs of most journalists. This is what I appreciated the most about the book – its practical nature (the title doesn’t lie!) Machlis focuses on the concepts that data journalists most frequently encounter and spends little to no time on those they don’t…I also appreciated Chapter 17, "An R Project from Start to Finish." This chapter is exactly why I’ve wanted a journalism-specific Intro to R project that I can recommend to my colleagues" ~Ryann Jones, Deputy Editor, Data at ProPublica"I like the book. It’s conversationally written, it walks you through common problems in data journalism and for the most part uses the most common libraries to analyze and visualize data…The book’s instructional approach is the real value – it seems aimed at an audience that needs a narrative in order to understand code and analysis. Conveniently, that pretty well describes journalism students and working professionals…I would recommend publication. It advances the field of data journalism and presents a solid text for instructors or practitioners who are interested in R for analysis." ~Matthew Waite"I NEED THIS BOOK. I may adopt it as a textbook." ~Alberto Cairo, University of Miami"I’m reading this book now and it is terrific. Highly recommended for anyone interested in learning R. I will be using this book in my Data Analysis for Journalists class in the spring." ~Rob Wells, University of Arkansas"Sharon Machlis' 'Practical R for Mass Communication and Journalism' is based on the author's workshops for journalists. This book dives straight into doing the kinds of things a busy reporter or news analyst needs to do to meet a 5:00 pm deadline: data cleaning, presentation-quality graphics, and maps take precedence over control flow or the niceties of variable scope. I particularly enjoyed the way each chapter starts with a realistic project and works through what's needed to build it. People who've never programmed before will be a little intimidated by how many packages they need to download if they try to work through the material on their own, but the instructions are clear, and the author's enthusiasm for her material shines through in every example." ~Greg Wilson, RStudioTable of ContentsIntroduction. Get Started With R in a Few Easy Steps. See How Much You Can Do in a Few Lines of Code. Import data into R. Project: Snowfall data; Skill: Basic data exploration. Project: Raw Snowfall data; Skill: Reshape data. Project: Airport Delays by Airline; Skill: Analyze data by groups. Map Median: Household Income; Skills: Simple mapping, saving graphics. Population Density and Election Results: Is There a Relationship?; Skills: Joining tables, correlations, basic linear regression. Easily Reproducible Reports With R Markdown; Skills: Generate a Word doc or HTML file from an R script.

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Book SynopsisAbout our author The late Neil A. Weiss received his Ph.D. from UCLA and subsequently accepted an assistant professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss taught statistics, probability, and mathematics, from the freshman level to the advanced graduate level, for more than 30 years. In recognition of his excellence in teaching, Dr. Weiss received the Dean's Quality Teaching Award from the ASU College of Liberal Arts and Sciences. He also was runner-up twice for the Charles Wexler Teaching Award in the ASU School of Mathematical and Statistical Sciences. Dr. Weiss's comprehensive knowledge and experience ensure that his texts are mathematically and statistically accurate, as well as pedagogically sound. In addition to his numerous research publications, Dr. Weiss was the author of A Course in Probability (Addison-Wesley, 2006). He alsoTable of Contents PART I: Introduction 1. The Nature of Statistics PART II: Descriptive Statistics 2. Organizing Data 3. Descriptive Measures PART III: Probability, Random Variables, and Sampling Distributions 4. Probability Concepts 5. Discrete Random Variables 6. The Normal Distribution 7. The Sampling Distribution of the Sample Mean PART IV: Inferential Statistics 8. Confidence Intervals for One Population Mean 9. Hypothesis Tests for One Population Mean 10. Inferences for Two Population Means 11. Inferences for Population Standard Deviations 12. Inferences for Population Proportions 13. Chi-Square Procedures PART V: Regression, Correlation, and ANOVA 14. Descriptive Methods in Regression and Correlation 15. Inferential Methods in Regression and Correlation 16. Analysis of Variance (ANOVA) PART VI: Multiple Regression and Model Building; Experimental Design and ANOVA MODULE A: Multiple Regression Analysis MODULE B: Model Building in Regression MODULE C: Design of Experiments and Analysis of Variance Answers to Selected Exercises Index Appendix A: Statistical Tables Appendix B: Answers to Selected Exercises

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Book SynopsisAbout our author Mario F. Triola is a Professor Emeritus of Mathematics at Dutchess Community College, where he has taught statistics for over 30 years. Marty also is the author of Elementary Statistics, 14th Edition, Elementary Statistics Using Excel, 7th Edition and Elementary Statistics Using the TI-83/84 Plus Calculator, 5th Edition. He is a coauthor of Biostatistics for the Biological and Health Sciences, 2nd Edition, Statistical Reasoning for Everyday Life, 5th Edition and Business Statistics. Essentials of Statistics is currently available as a Global Edition, and it has been translated into several foreign languages. Marty designed the original Statdisk statistical software, and he has w

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Book SynopsisLarson/Edwards' CALCULUS, 11E, INTERNATIONAL METRIC EDITION expertly combines the printed textbook and technology to deliver everything you need to master the material and pass the class. Stepped-out solution videos with instruction are available at CalcView.com for selected exercises throughout the text, and the website CalcChat.com presents free solutions to all of the odd-numbered exercises in the text.Table of ContentsP. PREPARATION FOR CALCULUS. Graphs and Models. Linear Models and Rates of Change. Functions and Their Graphs. Review of Trigonometric Functions. Review Exercises. P.S. Problem Solving. 1. LIMITS AND THEIR PROPERTIES. A Preview of Calculus. Finding Limits Graphically and Numerically. Evaluating Limits Analytically. Continuity and One-Sided Limits. Infinite Limits. Section Project: Graphs and Limits of Trigonometric Functions. Review Exercises. P.S. Problem Solving. 2. DIFFERENTIATION. The Derivative and the Tangent Line Problem. Basic Differentiation Rules and Rates of Change. Product and Quotient Rules and Higher-Order Derivatives. The Chain Rule. Implicit Differentiation. Section Project: Optical Illusions. Related Rates. Review Exercises. P.S. Problem Solving. 3. APPLICATIONS OF DIFFERENTIATION. Extrema on an Interval. Rolle's Theorem and the Mean Value Theorem. Increasing and Decreasing Functions and the First Derivative Test. Section Project: Even Fourth-Degree Polynomials. Concavity and the Second Derivative Test. Limits at Infinity. A Summary of Curve Sketching. Optimization Problems. Section Project: Minimum Time. Newton's Method. Differentials. Review Exercises. P.S. Problem Solving. 4. INTEGRATION. Antiderivatives and Indefinite Integration. Area. Riemann Sums and Definite Integrals. The Fundamental Theorem of Calculus. Section Project: Demonstrating the Fundamental Theorem. Integration by Substitution. Review Exercises. P.S. Problem Solving. 5. LOGARITHMIC, EXPONENTIAL, AND OTHER TRANSCENDENTAL FUNCTIONS. The Natural Logarithmic Function: Differentiation. The Natural Logarithmic Function: Integration. Inverse Functions. Exponential Functions: Differentiation and Integration. Bases Other than e and Applications. Section Project: Using Graphing Utilities to Estimate Slope. Indeterminate Forms and L���Hopital���s Rule. Inverse Trigonometric Functions: Differentiation. Inverse Trigonometric Functions: Integration. Hyperbolic Functions. Section Project: Mercator Map. Review Exercises. P.S. Problem Solving. 6. DIFFERENTIAL EQUATIONS. Slope Fields and Euler's Method. Growth and Decay. Separation of Variables and the Logistic Equation. First-Order Linear Differential Equations. Section Project: Weight Loss. Review Exercises. P.S. Problem Solving. 7. APPLICATIONS OF INTEGRATION. Area of a Region Between Two Curves. Volume: The Disk Method. Volume: The Shell Method. Section Project: Saturn. Arc Length and Surfaces of Revolution. Work. Section Project: Pyramid of Khufu. Moments, Centers of Mass, and Centroids. Fluid Pressure and Fluid Force. Review Exercises. P.S. Problem Solving. 8. INTEGRATION TECHNIQUES AND IMPROPER INTEGRALS. Basic Integration Rules. Integration by Parts. Trigonometric Integrals. Section Project: The Wallis Product. Trigonometric Substitution. Partial Fractions. Numerical Integration. Integration by Tables and Other Integration Techniques. Improper Integrals. Review Exercises. P.S. Problem Solving. 9. INFINITE SERIES. Sequences. Series and Convergence. Section Project: Cantor's Disappearing Table. The Integral Test and p-Series. Section Project: The Harmonic Series. Comparisons of Series. Alternating Series. The Ratio and Root Tests. Taylor Polynomials and Approximations. Power Series. Representation of Functions by Power Series. Taylor and Maclaurin Series. Review Exercises. P.S. Problem Solving. 10. CONICS, PARAMETRIC EQUATIONS, AND POLAR COORDINATES. Conics and Calculus. Plane Curves and Parametric Equations. Section Project: Cycloids. Parametric Equations and Calculus. Polar Coordinates and Polar Graphs. Section Project: Cassini Oval. Area and Arc Length in Polar Coordinates. Polar Equations of Conics and Kepler's Laws. Review Exercises. P.S. Problem Solving. 11. VECTORS AND THE GEOMETRY OF SPACE. Vectors in the Plane. Space Coordinates and Vectors in Space. The Dot Product of Two Vectors. The Cross Product of Two Vectors in Space. Lines and Planes in Space. Section Project: Distances in Space. Surfaces in Space. Cylindrical and Spherical Coordinates. Review Exercises. P.S. Problem Solving. 12. VECTOR-VALUED FUNCTIONS. Vector-Valued Functions. Section Project: Witch of Agnesi. Differentiation and Integration of Vector-Valued Functions. Velocity and Acceleration. Tangent Vectors and Normal Vectors. Arc Length and Curvature. Review Exercises. P.S. Problem Solving. 13. FUNCTIONS OF SEVERAL VARIABLES. Introduction to Functions of Several Variables. Limits and Continuity. Partial Derivatives. Differentials. Chain Rules for Functions of Several Variables. Directional Derivatives and Gradients. Tangent Planes and Normal Lines. Section Project: Wildflowers. Extrema of Functions of Two Variables. Applications of Extrema of Functions of Two Variables. Section Project: Building a Pipeline. Lagrange Multipliers. Review Exercises. P.S. Problem Solving. 14. MULTIPLE INTEGRATION. Iterated Integrals and Area in the Plane. Double Integrals and Volume. Change of Variables: Polar Coordinates. Center of Mass and Moments of Inertia. Section Project: Center of Pressure on a Sail. Surface Area. Section Project: Surface Area in Polar Coordinates. Triple Integrals and Applications. Triple Integrals in Cylindrical and Spherical Coordinates. Section Project: Wrinkled and Bumpy Spheres. Change of Variables: Jacobians. Review Exercises. P.S. Problem Solving. 15. VECTOR ANALYSIS. Vector Fields. Line Integrals. Conservative Vector Fields and Independence of Path. Green's Theorem. Section Project: Hyperbolic and Trigonometric Functions. Parametric Surfaces. Surface Integrals. Section Project: Hyperboloid of One Sheet. Divergence Theorem. Stokes' Theorem. Review Exercises. Section Project: The Planimeter. P.S. Problem Solving. 16. SECOND ORDER DIFFERENTIAL EQUATIONS* ONLINE. Exact First-Order Equations. Second-Order Homogeneous Linear Equations. Second-Order Nonhomogeneous Linear Equations. Section Project: Parachute Jump. Series Solutions of Differential Equations. Review Exercises. P.S. Problem Solving. APPENDIX. A. Proofs of Selected Theorems. B. Integration Tables. C. Precalculus Review (Web). C.1. Real Numbers and the Real Number Line. C.2. The Cartesian Plane. D. Rotation and the General Second-Degree Equation (Web). E. Complex Numbers (Web). F. Business and Economic Applications (Web). G. Fitting Models to Data (Web).

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Book SynopsisDiscover the utility of your organization's data with Microsoft Power BI In Beginning Power BI for Business Users: Learning to Turn Data into Insights, accomplished data professional and business intelligence expert Paul Fuller delivers an intuitive and accessible handbook for professionals seeking to use Microsoft's Power BI to access, analyze, understand, report, and act on the data available to their organizations. In the book, you'll discover Power BI's robust feature set, learn to ingest and model data, visualize and report on that data, and even use the DAX scripting language to unlock still more utility from Microsoft's popular program. Beginning with general principles geared to readers with no or little experience with reporting or data analytics tools, the author walks you through how to manipulate common, publicly available data sourcesincluding Excel files and relational databases. You'll also learn to: Use the included and testedTable of ContentsIntroduction xxi Part 1: Introduction Chapter 1: Introducing Power BI 3 What Is Power BI? 3 Why Would I Use Power BI? 7 But Why? 7 Disconnected Data 8 Fixed Formulas 9 Ten Reasons Why Power BI Transforms Your Work 10 Will I Still Use Excel? 12 How Much Is this Going to Cost? 14 Where Do We Go from Here? 16 Chapter 2: From Data to Insight 17 Three Guiding Principles 17 Distinguishing Data, Information, and Knowledge 18 Follow a Consistent, Proven Method 21 Data Sources 21 Files 21 Databases 22 Online Services 23 Plan Ahead 23 Import Data 25 Prepare Data 26 Model Data 28 Report Data 29 Analyze Data 30 Use Visualizations Well 31 Three Ways to Ruin Visual Analytics 32 Use as Many Cool Gadgets as You Can Find 32 Overwhelm the User with Tons of Detail 32 Pick the Wrong Tool for the Job 34 Four Ways to Improve Visual Analytics 35 Reduce the Nondata Pixels 35 Enhance the Data Pixels 36 Conclusion 38 Part 2: Power BI Guided Walk-Throughs Chapter 3: Let’s Take a Flyover! 41 Getting Connected 41 A Quick Tour of the Power BI Service 42 Frequented Hotspots of Power BI 42 Adding Sample Content 43 Understanding the Power BI Service Interface 44 Highlighting 47 Slicers 50 Filters 52 Drill-Down 54 Dashboards 55 Drill-Through 58 Visibility 59 Show as Table 59 Sorting Visuals 60 Filtering— One More Time 61 Power BI Building Blocks 61 Flyover of Power BI Desktop 62 Navigating Power BI Desktop 63 Conclusion 65 Chapter 4: Building Your First Report 67 Connecting to a Data Source 67 Examining the Data Model 68 Exploring the Data 75 Building Your Report 85 Designing for Mobile Devices 101 Conclusion 102 Chapter 5: Preparing Data 103 GDP Data 103 Power Query Overview 105 Data Arrangement Steps 106 Rename Query 106 Remove Rows 106 Remove Columns 107 Applied Steps So Far 107 Promote Headers 108 Renaming Columns 108 Empty Values 109 Handling Aggregated Data 109 Filtering Rows 110 Unpivoting Data 110 Change Column Data Type 112 Changing Values in Columns 112 Duplicating Columns 113 Multiply by a Million 113 Removing Implicit Measures 114 Column Formatting 115 Calculated Columns 115 Add Previous Year Column 116 Hiding Columns 117 LOOKUPVALUE Function 118 DIVIDE Function 119 Visualize Our GDP Data 120 Where Are We? 121 Cleaning Messy Data 122 Handle Many-to-Many Relationships 123 Duplicate a Query 125 Split Column 125 Format Column 127 Remove Duplicates 127 Index Column 128 Merge Data 128 Applying Changes 129 Finding the Power Query Button 131 Simple Cleanup Tasks 131 Replacing Values 132 Custom Columns 133 More Cleanup 135 Cleaning Date Columns 136 Conclusion 138 Chapter 6: Modeling Data 139 Dimensional Modeling 140 Why Does This Matter? 143 Makes Sense to You 143 Cross-Business Process Analysis 144 Flexible Grouping 144 Performance for Power BI 144 Facts 145 Types of Facts 146 Granularity 146 Relationships Between Facts (Never!) 147 Dimensions 148 Using Integer Keys for Relationships 149 Hierarchies in Dimensions 149 Date Dimensions 150 Power Query and Data Modeling 151 How to Build a Date Dimension 152 Import a Date Table from SQL Server Database 153 Create a Date Dimension with Power Query 155 Create a Date Dimension with DAX 158 Sort by Column 161 Mark It as a Date Table 161 How to Arrange into a Star- Schema 161 Create a State Dimension 162 Create a GDP Category Dimension 163 Add a New StateID Foreign Key to Our Fact Table 163 Unpivot the GDP Year Values 164 Putting It All into Action 166 Conclusion 167 Part 3: Going Deeper Into Power BI Chapter 7: Relationships and Filtering 171 Filtering Through Relationships 171 Visuals Interact Independently 174 The Direction of Relationships 176 Bidirectional Filtering 179 Report Filter Types 181 Visual Filters 181 Date Filtering 182 Numeric Filtering 182 Text Filtering 183 Page and Report Filters 185 Controlling the Use of Filters 185 Conclusion 186 Chapter 8: Enhancing Your Report 187 Configuring Drill- Down 187 Configuring Drill- Through 190 Buttons 193 Bookmarks 195 Personal Bookmarks vs. Report Bookmarks 199 Selections and Visibility 201 Conclusion 205 Chapter 9: Refreshing, Sharing, and Collaborating 207 Refreshing Data 207 Configuring Data Source Credentials 210 Power BI Data Gateway 213 Scheduling Refresh 214 Dataset Modes 216 Sharing and Collaborating 216 Workspaces 216 Creating Workspaces 217 Publishing 217 Security and Permission Levels 219 Power BI Apps 223 Sharing 230 Summary 232 Chapter 10: Introducing Dax 233 Setup 233 Calculated Columns 235 How to Create a Calculated Column 236 DAX Measures 240 COUNTROWS and DISTINCTCOUNT 244 Filter Context 246 CALCULATE Function 249 Conclusion 250 Chapter 11: Conclusion 251 Where Does My Organization Begin? 251 Delivery Strategy 251 Business-Led Self-Service 252 IT-Managed Self-Service 253 Corporate BI 253 Which Delivery Strategy Is Right for My Organization? 253 Where Do I Go from Here? 254 Top Gurus 254 Advice 254 Index 257

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Book SynopsisA prize-winning biography of one of the foremost intellects of the twentieth century: Claude Shannon, the neglected architect of the Information Age.Trade Review‘A long overdue, insightful and humane portrait of this eccentric and towering genius.’ -- Walter Isaacson, bestselling author of STEVE JOBs‘A welcome and inspiring account of a largely unsung hero - unsung because, the authors suggest, he accomplished something so fundamental that it’s difficult to imagine a world without it.' -- Kirkus Reviews‘An exceptionally elegant and authoritative portrait… Sonni and Goodman’s elucidations of Claude Shannon’s theories are gems of conciseness and clarity.' -- Sylvia Nasar, author of the bestselling A BEAUTIFUL MIND, winner of the National Books Critics Award

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Basic Mathematics teaches you all the maths you need for everyday situations. If you are terrified by maths, this is the book for you.Do you shy away from using numbers? Basic Mathematics can help. An easy-to-follow guide, it will ensure you gain the confidence you need to tackle maths and overcome your fears. It offers simple explanations of all the key areas, including decimals, percentages, measurements and graphs, and applies them to everyday situations, games and puzzles to help you understand mathematics quickly and enjoyably.Everything you need is here in this one book. Each chapter includes clear explanations, worked examples and test questions. At the end of the book there are challenges and games to give you new and interesting ways to practise your new skills.

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Book SynopsisExam board: Cambridge Assessment International EducationLevel: A LevelSubject: MathematicsFirst teaching: September 2018First exams: Summer 2020Reinforce learning and deepen understanding of the key concepts covered in the latest syllabus; an ideal course companion or homework book for use throughout the course.- Develop and strengthen skills and knowledge with a wealth of additional exercises that perfectly supplement the Student's Book. - Build confidence with extra practice for each lesson to ensure that a topic is thoroughly understood before moving on. - Ensure students know what to expect with hundreds of rigorous practice and exam-style questions. - Keep track of students' work with ready-to-go write-in exercises. - Save time with all answers available for free online: www.hoddereducation.co.uk/cambridgeextras.This book covers the syllabus content for Probability and Statistics 1, including representation of data, permutations and combinations, probability, discrete random variables and the normal distribution. This title has not been through the Cambridge Assessment International Education endorsement process.Available in this series:Five textbooks fully covering the latest Cambridge International AS & A Level Mathematics syllabus (9709) are accompanied by a Workbook, and Student and Whiteboard eTextbooks.Pure Mathematics 1: Student Textbook (ISBN 9781510421721), Student eTextbook (ISBN 9781510420762), Whiteboard eTextbook (ISBN 9781510420779), Workbook (ISBN 9781510421844)Pure Mathematics 2 and 3: Student Textbook (ISBN 9781510421738), Student eTextbook (ISBN 9781510420854), Whiteboard eTextbook (ISBN 9781510420878), Workbook (ISBN 9781510421851)Mechanics: Student Textbook (ISBN 9781510421745), Student eTextbook (ISBN 9781510420953), Whiteboard eTextbook (ISBN 9781510420977), Workbook (ISBN 9781510421837)Probability & Statistics 1: Student Textbook (ISBN 9781510421752), Student eTextbook (ISBN 9781510421066), Whiteboard eTextbook (ISBN 9781510421097), Workbook (ISBN 9781510421875)Probability & Statistics 2: Student Textbook (ISBN 9781510421776), Student eTextbook (ISBN 9781510421158), Whiteboard eTextbook (ISBN 9781510421165), Workbook (9781510421882)

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Book SynopsisThis collection presents the major mathematical works of Isadore Singer, selected by Singer himself, and organized thematically into three volumes: 1. Functional analysis, differential geometry and eigenvalues 2. Index theory 3. Gauge theory and physics Each volume begins with a commentary (and in the first volume, a short biography of Singer), and then presents the works on its theme in roughly chronological order.

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Book SynopsisWhat are the strangest numbers? Where do numbers come from? Can maths guarantee riches? Why are three dimensions not enough? Can a butterfly's wings really cause a hurricane? Can maths predict the future? In How Big is Infinity?, acclaimed writer Tony Crilly distills the wisdom of some of the greatest minds in history to help provide answers some of the most perplexing, stimulating and surprising questions in mathematics.Table of ContentsIntroduction. What is mathematics for? - An introduction to purposes and prospects. Where do numbers come from? - From notches on bones to hexadecimals. Why are primes the atoms of mathematics? - Building blocks and the fundamental theorem of arithmetic. Which are the strangest numbers? - Real, irrational and transcendental numbers. Are imaginary numbers truly imaginary? - From the imaginary 'I' to octonions. How big is infinity? - Set theory and the infinity revolution. Where do parallel lines meet? - The birth of new geometries. What is the mathematics of the universe? - The Calculus miracle. Are statistics lies? - Data, proof and 'damned lies'. Can mathematics guarantee riches? - Uncertainty, chance and probability theory. Is there a formula for everything? - Mathematical recipes and the search for knowledge. Why are three dimensions not enough? - Higher dimensions, monster curves and fractals. Can a butterfly's wings really cause a hurricane? - Chaos theory, weather equations and strange attractors. Can we create an unbreakable code? - Ciphers, the Enigma machine and quantum computers. Is mathematics beautiful? - Music, art, golden numbers and the Fibonacci sequence. Can mathematics predict the future? - Mathematical models, simulations and game theory. What shape is the universe? - Topology, manifolds and the Poincare conjecture. What is symmetry? - Patterns, dualities and the fundamental nature of reality. Is mathematics true? - From Plato's reality to Godel's incompleteness theorems. Is there anything left to solve? - The great unsolved problems and the future of mathematics. Glossary. Index.

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Book SynopsisCGP have knocked it out of the park with this Exam Practice Workbook for the SQA Higher Maths course. It's loaded with realistic exam-style questions on a wide range of Higher Maths topics - perfect practice for the tough exams! For more essential revision for Higher Maths, check out our brilliant Revision Guide (ISBN: 9781782949602)

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Book SynopsisSome people fear and mistrust numbers. Others want to use them for everything. After a long career as a statistician, Paul Goodwin has learned the hard way that the ones who want to use them for everything are a very good reason for the rest of us to fear and mistrust them. Something Doesn't Add Up is a fieldguide to the numbers that rule our world, even though they don't make sense. Wry, witty and humane, Goodwin explains mathematical subtleties so painlessly that you hardly need to think about numbers at all. He demonstrates how statistics that are meant to make life simpler often make it simpler than it actually is, but also reveals some of the ways we really can use maths to make better decisions. Enter the world of fitness tracking, the history of IQ testing, China's social credit system, Effective Altruism, and learn how someone should have noticed that Harold Shipman was killing his patients years before they actually did. In the right hands, maths is a useful tool. It's just a pity there are so many of the wrong hands about.Trade ReviewPraise for Forewarned: A Sceptic's Guide to Prediction The book is awash with entertaining examples of predictions that were astoundingly accurate and others that were spectacularly wrong. * Irish Times *

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Book SynopsisAchieve the best grades in 2025 or 2026 with this unbeatable course book from CGP!This book covers all the content needed for AS and Year 1 of the Edexcel Pure Maths A-Level course and is fully up to date for the latest specifications. It has crystal-clear notes on all the theory for every topic, including annotated worked examples and explanations; hundreds of challenging questions for every chapter, including problem-solving and modelling; a realistic Practice Paper with a complete mark scheme; and a free Online Edition to read on PC, Mac or tablet (use the unique code printed inside the cover to gain full access).For full A-Level Maths coverage don't miss the Year 1/AS Statistics and Mechanics Student Textbook (9781789088403), and Year 2 Student Textbooks for Pure Maths (9781789088410) and Statistics and Mechanics (9781789088427).

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Book SynopsisThe quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains active today, particularly in the development of machine learning.Classical and Modern Optimization presents a self-contained overview of classical and modern ideas and methods in approaching optimization problems. The approach is rich and flexible enough to address smooth and non-smooth, convex and non-convex, finite or infinite-dimensional, static or dynamic situations. The first chapters of the book are devoted to the classical toolbox: topology and functional analysis, differential calculus, convex analysis and necessary conditions for differentiable constrained optimization. The remaining chapters are dedicated to more specialized topics and applications.Valuable to a wide audience, including students in mathematics, engineers, data scientists or economists, Classical and Modern Optimization contains more than 200 exercises to assist with self-study or for anyone teaching a third- or fourth-year optimization class.

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Book SynopsisFrom ancient Babylon to the last great unsolved problems, Ian Stewart brings us his definitive history of mathematics. In his famous straightforward style, Professor Stewart explains each major development - from the first number systems to chaos theory - and considers how each affected society and changed everyday life forever. Maintaining a personal touch, he introduces all of the outstanding mathematicians of history, from the key Babylonians, Greeks and Egyptians, via Newton and Descartes, to Fermat, Babbage and Godel, and demystifies maths' key concepts without recourse to complicated formulae. Written to provide a captivating historic narrative for the non-mathematician, Taming the Infinite: The Story of Mathematics is packed with fascinating nuggets and quirky asides, and contains 100 illustrations and diagrams to illuminate and aid understanding of a subject many dread, but which has made our world what it is today.Trade Review'An engaging history of maths, guaranteed to illuminate even the most number-shy' Waterstone's Books Quarterly. * Waterstone's Books Quarterly *Table of ContentsPreface. Tokens, Tallies and Tablets. The Logic of Shape. Notations and Numbers. Lure of the Unknown. Eternal Triangles. Curves and Coordinates. Patterns in Numbers. The System of the World. Patterns in Nature. Impossible Quantities. Firm Foundations. Impossible Triangles. The Rise of Symmetry. Algebra Comes of Age. Rubber Sheet Geometry. The Fourth Dimension. The Shape of Logic. How Likely is That? Number Crunching. Chaos and Complexity. Further Reading. Index.

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Book SynopsisThis is a brand new edition of our popular Advanced Higher Mathematics Study Guide, which is fully up-to-date with the SQA changes. There is no shortcut to passing any course at CfE Advanced Higher level - to obtain a good pass students must revise consistently and regularly over the duration of the course. The aim of this CfE Advanced Higher Mathematics Study Guide from BrightRED is to bring together, in one volume, concise coverage of the SQA Advanced Higher course material. Written by the authors of our bestselling Advanced Higher Mathematics Revision book, this completely new title will be the ONLY Study Guide available for CfE Advanced Higher Mathematics. The book will also be fully supported with a wealth of extra material, visual aids, calculators and video links on the free BrightRED Digital Zone.Trade ReviewTwo 5* reviews on Amazon.co.ukTable of ContentsIntroduction, Algebra, Differentiation, Functions, Integration, Equations, Matrices, Complex Numbers, Sequences and Series, Vectors, Differential Equations, Number Theory and Proof, Appendices, Answers, Index

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Book SynopsisSuitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books Trade ReviewFrom the reviews: "[the material is] superbly motivated with interest-grabbing examples... exercises excellent and plentiful." Edward Williams, University of Michigan-Dearborn, USA "... it is a notoriously hard task to introduce probability and statistics with a mix of intuition and mathematics to keep students motivated. Therefore, I very much welcome this book and recommend it as course material." Sara van de Geer, Leiden University, The Netherlands "This textbook provides a well-written first course in probability and statistics...It is a book that has been written based on the long teaching experience of the authors and I would certainly recommend it for university coursework." Short Book Reviews of the International Statistical Institute, December 2005 "This book has numerous quick exercises to give direct feedback to the students. … A website at www.springeronline.com/978-1-85233-896-1 gives access to the data files used in the text … . This will be a key text for undergraduates in computer science, physics, mathematics, chemistry, biology and business studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects." (Rainer Beedgen, Zentralblatt MATH, Vol. 1079, 2006) "The book is designed for a one-semester introductory course in probability and statistics basics for engineering students. … It can also be used by students in other more mathematically oriented majors such as applied mathematics with more emphasis on the mathematics and additional coverage in topics such as combinatorics, conditional expectation, and generating functions. … More elaborate exercises and real datasets are given at the end of each chapter." (Arthur B. Yeh, Technometrics, Vol. 49 (3), August, 2007)Table of ContentsWhy probability and statistics?.- Outcomes, events, and probability.- Conditional probability and independence.- Discrete random variables.- Continuous random variables.- Simulation.- Expectation and variance.- Computations with random variables.- Joint distributions and independence.- Covariance and correlation.- More computations with more random variables.- The Poisson process.- The law of large numbers.- The central limit theorem.- Exploratory data analysis: graphical summaries.- Exploratory data analysis: numerical summaries.- Basic statistical models.- The bootstrap.- Unbiased estimators.- Efficiency and mean squared error.- Maximum likelihood.- The method of least squares.- Confidence intervals for the mean.- More on confidence intervals.- Testing hypotheses: essentials.- Testing hypotheses: elaboration.- The t-test.- Comparing two samples.

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Book Synopsis2024 Nautilus Book Award Winner * The Marginalian Favorite Books of 2023An electrifying introduction to complexity theory, the science of how complex systems behave, that explains the interconnectedness of all things and that Deepak Chopra says, “will change the way you understand yourself and the universe.”Nothing in the universe is more complex than life. Throughout the skies, in oceans, and across lands, life is endlessly on the move. In its myriad forms—from cells to human beings, social structures, and ecosystems—life is open-ended, evolving, unpredictable, yet adaptive and self-sustaining. Complexity theory addresses the mysteries that animate science, philosophy, and metaphysics: how this teeming array of existence, from the infinitesimal to the infinite, is in fact a seamless living whole and what our place, as conscious beings, is within it.The implications of complexity theory are profound, providing insight into everything from the permeable boundaries of our bodies to the nature of consciousness. Notes on Complexity is an invitation to trade our limited, individualistic view for the expansive perspective of a universe that is dynamic, cohesive, and alive—a whole greater than the sum of its parts. Physician, scientist, and philosopher Neil Theise takes us to the exhilarating frontiers of human knowledge and in the process restores wonder and meaning to our experience of the everyday.

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Book SynopsisThis book, the second in a two-volume set, provides an introduction to the basics of (mainly) non-relativistic quantum mechanics. While the first volume addresses the basic principles, this second volume discusses applications and extensions to more complex problems. In addition to topics dealt with in traditional quantum mechanics texts, such as symmetries or many-body problems, it also treats issues of current interest such as entanglement, Bell’s inequality, decoherence and various aspects of quantum information in detail. Furthermore, questions concerning the basis of quantum mechanics and epistemological issues which are relevant e.g. to the realism debate are discussed explicitly. A chapter on the interpretations of quantum mechanics rounds out the book. Readers are introduced to the requisite mathematical tools step by step. In the appendix, the most relevant mathematics is compiled in compact form, and more advanced topics such as the Lenz vector, Hardy’s experiment and Shor’s algorithm are treated in more detail. As an essential aid to learning and teaching, 130 exercises are included, most of them with solutions. This revised second edition is expanded by an introduction into some ideas and problems of relativistic quantum mechanics. In this second volume, an overview of quantum field theory is given and basic conceptions of quantum electrodynamics are treated in some detail. Originally written as a course for students of science education, the book addresses all those science students and others who are looking for a reasonably simple, fresh and modern introduction to the field.Trade Review“This book continues the excellent introduction to quantum mechanics of the first volume ... suited for beginners to get first insights which may be deepened reading the appendices. The two volumes can be best recommended generally and especially for self studies.” (K.-E. Hellwig, zbMATH 1445.81002, 2020)Table of ContentsOne-Dimensional Piecewise-Constant Potentials.- Angular Momentum.- The Hydrogen Atom.- The Harmonic Oscillator.- Perturbation Theory.- Entanglement, EPR, Bell.- Symmetries and Conservation Laws.- The Density Operator.- Identical Particles.- Decoherence.- Scattering.- Quantum Information.- Is Quantum Mechanics Complete?.- Interpretations of Quantum Mechanics.

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Book SynopsisKeeping students involved and actively learning is challenging. Instructors in computer science are aware of the cognitive value of modelling puzzles and often use logical puzzles as an efficient pedagogical instrument to engage students and develop problem-solving skills. This unique book is a comprehensive resource that offers teachers and students fun activities to teach and learn logic. It provides new, complete, and running formalisation in Propositional and First Order Logic for over 130 logical puzzles, including Sudoku-like puzzles, zebra-like puzzles, island of truth, lady and tigers, grid puzzles, strange numbers, or self-reference puzzles. Solving puzzles with theorem provers can be an effective cognitive incentive to motivate students to learn logic. They will find a ready-to-use format which illustrates how to model each puzzle, provides running implementations, and explains each solution. This concise and easy-to-follow textbook is a much-needed support tool for students willing to explore beyond the introductory level of learning logic and lecturers looking for examples to heighten student engagement in their computer science courses. Trade Review“The purpose of this book is to introduce first-order logic (FOL) to newcomers. … The book is a treasure trove of puzzles like this. … All of these are motivated in an approachable, fun way. … the book is a hands-on guide to Prover9 and Mace4 … . It is quite valuable to have so many puzzles in a single book.” (Jesse Adam Alama, Mathematical Reviews, October, 2022)Table of ContentsPreface.- Getting Started with Prover9 and Mace4.- Micro Arithmetic Puzzles.- Strange Numbers.- Practical Puzzles.- Lady and Tigers.- Einstein Puzzles.- Island of Truth.- Love and Marriage.- Grid Puzzles.- Japanese Puzzles.- Russian Puzzles.- Polyomino Puzzles.- Self-reference and Other Puzzles.- Epigraph in Natural Language

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Book SynopsisThis book is dedicated to study the inverse problem of ordinary differential equations, that is it focuses in finding all ordinary differential equations that satisfy a given set of properties. The Nambu bracket is the central tool in developing this approach. The authors start characterizing the ordinary differential equations in R^N which have a given set of partial integrals or first integrals. The results obtained are applied first to planar polynomial differential systems with a given set of such integrals, second to solve the 16th Hilbert problem restricted to generic algebraic limit cycles, third for solving the inverse problem for constrained Lagrangian and Hamiltonian mechanical systems, fourth for studying the integrability of a constrained rigid body. Finally the authors conclude with an analysis on nonholonomic mechanics, a generalization of the Hamiltonian principle, and the statement an solution of the inverse problem in vakonomic mechanics.Trade Review“The book presents a new approach to … inverse problems, where the authors mainly use as an essential tool the Nambu bracket. They deduce new properties of this bracket, which plays a fundamental role in the proof of all the results and in their applications throughout the book. … The book is well written and contains new and valuable results in the development of the inverse problem in ordinary differential equations and its applications.” (Leonardo Colombo, Mathematical Reviews, January, 2017)Table of ContentsPreface.- 1.Differential Equations with Given Partial and First Integrals.- 2.Polynomial Vector Fields with Given Partial and First Integrals.- 3.16th Hilbert Problem for Algebraic Limit Cycles.- 4.Inverse Problem for Constrained Lagrangian Systems.- 5.Inverse Problem for Constrained Hamiltonian Systems.- 6.Integrability of the Constrained Rigid Body.- 7.Inverse Problem in the Vakonomic Mechanics.- Index.- Bibliography.

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Book SynopsisAbout The BookThe Essentials Of Vedic Mathematics is a book that shows you how to master Vedic mathematics independently, without the help of any expert. Vedic mathematics consists of sixteen sutras and sixteen sub-sutras. It is an ancient technique that can be very beneficial to people even today. The book shows you how to simplify the most basic arithmetic operations and also deal with complex mathematical concepts such as quadratic equations, factorization of cubic equations and much more.Considering that Vedic mathematics is now being used extensively even by those students who are preparing for a range of competitive examinations, it is important that you be able to use this method to your advantage. Vedic Mathematics is now used in preparations for the CAT, SAT, XAT, MAT, banking entrance exams, engineering exams and many other similar competitive examinations. Keeping in mind just how important speed and reasoning are in such exams, the author shows you how to use these concepts to finish your paper quickly and correctly.The author has also included certain chapters in this book that will be helpful for those students who are preparing for their CBSE or ICSE examinations. The book is designed in such a way that it is useful and understandable to a wide audience.The first edition of The Essentials Of Vedic Mathematics was published by Rupa Publications India in 2013 and is available in paperback.Key Features The book is written with a simple and easily-comprehensible tone. It not only caters to those who are preparing for entrance exams, but also to those who are studying for school exams.

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