Maths for scientists Books
John Wiley & Sons Inc Modern Geometrical Optics
Book SynopsisFrom basic terms and concepts to advanced optimization techniques-a complete, practical introduction to modern geometrical optics Most books on geometrical optics present only matrix methods.Table of ContentsThe Nature of Light. Introduction to Imaging Systems. Paraxial Optics I. Paraxial Optics II. Matrix Methods. Exact Ray Tracing. Third-Order Optics. First-Order Design and y-y Diagrams. Optimization. Introduction to Lens Design. Appendices. Index.
£154.76
John Wiley & Sons Inc Planning Construction and Statistical Analysis of
Book SynopsisThe outgrowth of more than 40 years of experience teaching and consulting with students and active researchers in many disciplines, this is a useful guide for both students and active researchers to experimental design.Trade Review"…an excellent reference for statisticians and practitioners who would like to gain broad exposure to the tools available for studying relationships between qualitative and quantitative factors…" (Journal of the American Statistical Association, June 2005) “The level of detail is higher than in most other books on similar topics and therefore makes this one a useful reference tool.” (Short Book Reviews, Vol.25, No.1, April 2005) "I will instruct statistician reporting to me to get a copy of the book, and will keep the review copy readily available on my shelf…" (Technometrics, February 2005) "There is a moderate amount of material that is not in other design books…in addition to some tricks of the trade that appear to be new…practitioners…will find the book useful." (Journal of Quality Technology, October 2004) "...an excellent resource handbook for researchers and statisticians, providing them with the tools necessary to construct better experiments and plan more efficient investigations.” (CHOICE, October 2004)Table of ContentsPreface. Introduction. The Completely Randomized Design. Linear Models for Designed Experiments. Testing Hypotheses and Determining Sample Size. Methods of Reducing Unexplained Variation. Latin Squares. Split-Plot and Related Designs. Incomplete Block Designs. Repeated Teatments Designs. Factorial Experiments, the 2n System. Factorial Experiments, the 3n System. Analysis of Experiments Without Designed Error Terms. Confounding Effects with Blocks. Fractional Factorial Experiments. Response Surface Designs. Plackett-Burmann Hadamard Plans. The General Pn and Nonstandard Factorials. Factorial Experiments with Quantitative Factors. Plans for Which Run Order is Important. Supersaturated Plans. Sequences of Fractions of Factorials. Multi-Stage xperiments. Orthogonal Arrays and Related Structures. Factorial Plans Derived via Orthogonal Arrays. Experiments on the Computer.
£157.45
Wiley Approximation Theorems of Mathematical Statistics
Book SynopsisCovers a range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. This book emphasizes the manipulation of "probability" theorems to obtain "statistical" theorems.Trade Review"...even today it still provides a really good introduction into asymptotic statistics..."(Zentralblatt Math, Vol. 1001, No.01, 2003)Table of Contents1 Preliminary Tools and Foundations 1 1.1 Preliminary Notation and Definitions 1 1.2 Modes of Convergence of a Sequence of Random Variables 6 1.3 Relationships Among the Modes of Convergence 9 1.4 Convergence of Moments; Uniform Integrability 13 1.5 Further Discussion of Convergence in Distribution 16 1.6 Operations on Sequences to Produce Specified Convergence Properties 22 1.7 Convergence Properties of Transformed Sequences 24 1.8 Basic Probability Limit Theorems: The WLLN and SLLN 26 1.9 Basic Probability Limit Theorems: The CLT 28 1.10 Basic Probability Limit Theorems: The LIL 35 1.11 Stochastic Process Formulation of the CLT 37 1.12 Taylor’s Theorem; Differentials 43 1.13 Conditions for Determination of a Distribution by Its Moments 45 1.14 Conditions for Existence of Moments of a Distribution 46 1.15 Asymptotic Aspects of Statistical Inference Procedures 47 1.P Problems 52 2 The Basic Sample Statistics 55 2.1 The Sample Distribution Function 56 2.2 The Sample Moments 66 2.3 The Sample Quantiles 74 2.4 The Order Statistics 87 2.5 Asymptotic Representation Theory for Sample Quantiles Order Statistics and Sample Distribution Functions 91 2.6 Confidence Intervals for Quantiles 102 2.7 Asymptotic Multivariate Normality of Cell Frequency Vectors 107 2.8 Stochastic Processes Associated with a Sample 109 2.P Problems 113 3 Transformations of Given Statistics 117 3.1 Functions of Asymptotically Normal Statistics: Univariate Case 118 3.2 Examples and Applications 120 3.3 Functions of Asymptotically Normal Vectors 122 3.4 Further Examples and Applications 125 3.5 Quadratic Forms in Asymptotically Multivariate Normal Vectors 128 3.6 Functions of Order Statistics 134 3.P Problems 136 4 Asymptotic Theory in Parametric Inference 138 4.1 Asymptotic Optimality in Estimation 138 4.2 Estimation by the Method of Maximum Likelihood 143 4.3 Other Approaches toward Estimation 150 4.4 Hypothesis Testing by Likelihood Methods 151 4.5 Estimation via Product-Multinomial Data 160 4.6 Hypothesis Testing via Product-Multinomial Data 165 4.P Problems 169 5 U-Statistics 171 5.1 Basic Description of U-Statistics 172 5.2 The Variance and Other Moments of a U-Statistic 181 5.3 The Projection of a U-Statistic on the Basie Observations 187 5.4 Almost Sure Behavior of U-Statistics 190 5.5 Asymptotic Distribution Theory of U-Statistics 192 5.6 Probability Inequalities and Deviation Probabilities for U-Statistics 199 5.7 Complements 203 5.P Problems 207 6 Von Mises Differentiable Statistical Functions 210 6.1 Statistics Considered as Functions of the Sample Distribution Function 211 6.2 Reduction to a Differential Approximation 214 6.3 Methodology for Analysis of the Differential Approximation 221 6.4 Asymptotic Properties of Differentiable Statistical Functions 225 6.5 Examples 231 6.6 Complements 238 6.P Problems 241 7 M-Estimates 243 7.1 Basic Formulation and Examples 243 7.2 Asymptotic Properties of M-Estimates 248 7.3 Complements 257 7.P Problems 260 8 L-Estimates 8.1 Basic Formulation and Examples 262 8.2 Asymptotic Properties of L-Estimates 271 8.P Problems 290 9 R-Estimates 9.1 Basic Formulation and Examples 292 9.2 Asymptotic Normality of Simple Linear Rank Statistics 295 9.3 Complements 311 9.P Problems 312 10 Asymptotic Relative Efficiency 10.1 Approaches toward Comparison of Test Procedures 314 10.2 The Pitman Approach 316 10.3 The Chernoff Index 325 10.4 Bahadur’s “Stochastic Comparison,” 332 10.5 The Hodges-Lehmann Asymptotic Relative Efficiency 341 10.6 Hoeffding’s Investigation (Multinomial Distributions) 342 10.7 The Rubin‒Sethuraman “Bayes Risk” Efficiency 347 I0.P Problems 348 Appendix 351 References 553 Author Index 365 Subject Index 369
£126.85
John Wiley & Sons Inc Chemical Kinetics and Catalysis
Book SynopsisChemical kinetics involves the rates at which chemical reactions occur and helps explain many natural and mechanical phenomena. For instance, kinetics explains how pharmaceuticals function in a biological system and how pollutants produced by combustion engines are converted for release into the atmosphere.Trade Review"...compared to its predecessors, Dr. Masel's book stands out with its up-to-date content. The book will find readers in a variety of disciplines..." (Chemical Engineering Progress) "...comprehensive, up-to-date, and rigorous...an excellent text..." (Journal of Chemical Education, Vol. 79, No. 3, March 2002)Table of ContentsReview of Some Elementary Concepts. Analysis of Rate Data. Relationship Between Rates and Mechanisms. Prediction of the Mechanisms of Reactions. Review of Some Thermodynamics and Statistical Mechanics. Introduction to Reaction Rate Theory. Reactions as Collisions. Transition State Theory: The RRKM Model and Related Results. Why Do Reactions Have Activation Barriers? More About Activation Energies. Introduction to Catalysis. Solvents as Catalysts. Catalysis by Metals.
£175.46
John Wiley & Sons Inc Numerical and Analytical Methods for Scientists
Book SynopsisThis book is written from the perspective of a physicist, not a mathematician, with an emphasis on modern practical applications in the physical and engineering sciences. The book itself is essentially software, written in the language of Mathematica, the widely used and highly praised Mathematica software package.Trade Review"...a very valuable addition to the literature of the field..." (Zentralblatt Math, Vol. 1029, 2004) "...offers a comprehensive Mathematica-based guide to the analytical and numerical methods used every day...includes many exercises and worked examples..." (The Mathematica Journal, Vol. 9 No. 1)Table of ContentsPreface. Ordinary Differential Equations in the Physical Sciences. Fourier Series and Transforms. Introduction to Linear Partial Differential Equations. Eigenmode Analysis. Partial Differential Equations in Infinite Domains. Numerical Solution of Linear Partial Differential Equations. Nonlinear Partial Differential Equations. Introduction to Random Processes. An Introduction to Mathematica (Electronic Version Only). Appendix: Finite-Differenced Derivatives. Index.
£170.06
John Wiley & Sons Inc Analysis and Purification Methods in
Book SynopsisDescribes various analytical techniques and systems for the development, validation, quality control, purification, and physicochemical testing of combinatorial libraries. This book provides coverage of applications of Nuclear Magnetic Resonance (NMR), liquid chromatography/mass spectrometry (LC/MS), and Fourier Transform Infrared (FTIR).Trade Review"…a timely and valuable volume that would be an excellent addition to university libraries and the collections of individuals…" (E-STREAMS, February 2005) "...a useful book for chemists entering the field from either analytical or synthetic organic chemistry backgrounds.” (Angewandte Chemie International Edition, September 6, 2004) "This useful volume is a worthwhile addition to institute libraries as well as to the libraries students and researchers who are working in analytical chemistry, medicinal chemistry, organic chemistry, biotechnology…" (Energy Sources, August 2004)Table of ContentsPreface. Contributors. PART I: ANALYSIS FOR FEASIBILITY AND OPTIMIZATION OF LIBRARY SYNTHESIS. Chapter 1. Quantitative Analysis in Organic Synthesis with NMR (L. Lucas & C. Larive). Chapter 2. 19F Gel-phase NMR Spectroscopy for Reaction Monitoring and Quantification of Resin Loading (J. Salvino). Chapter 3. The Application of Single-Bead FTIR and Color Test for Reaction Monitoring and Building Block Validation in Combinatorial Library Sysnthesis(J. Cournoyer, et al.). Chapter 4. HR-MAS NMR Analysis of Compounds Attached to Polymer Supports (M. Guinó & Y. de Miguel). Chapter 5. Multivariate Tools for Real-Time Monitoring and Optimization of Combinatorial Materials and Process Conditions (R. Potyrailo, et al.). Chapter 6. Mass Spectrometry and Soluble Polymeric Supports (C. Enjalbal, et al.). PART II: HIGH-THROUGHPUT ANALYSIS FOR LIBRARY QUALITY CONTROL. Chapter 7. High-Throughput NMR Techniques for Combinatorial Chemical Library Analysis (T. Hou & D. Raftery). Chapter 8. Micellar Electrokinetic Chromatography as a Tool for Combinatorial Chemistry Analysis: Theory and Applications (P. Simms). Chapter 9. Characterization of Split-Pool Encoded Combinatorial Libraries (J. Zhang & W. Fitch). PART III: HIGH-THROUGHPUT PURIFICATION TO IMPROVE LIBRARY QUALITY. Cha pter 10. Strategies and Methods for Purifying Organic Compounds and Combinatorial Libraries (J. Zhao, et al.). Chapter 11. HTP of Combinatorial Chemistry Libraries (J. Hochlowski). Chapter 12. Practical HPLC in High Throughput Analysis and Purification (H. Gumm & R. God). PART IV: ANALYSIS FOR COMPOUND STABILITY AND DRUGABILITY. Chapter 13. Organic Compound Stability in Large, Diverse Phatmaceutical Screening Collection (K. Morand & X. Cheng). Chapter 14. Quartz Crystal Microbalance in Biomolecular Recognition (M. Tseng, et al.). Chapter 15. High-Throughput Physicochemical Profiling: Potential and Limitations (B. Faller). Chapter 16. Solubility in the Design of Combinatorial Libraries (C. Lipinski). Chapter 17. High-Throughput Determination of Log D Values by LC/MS Method (J. Villena, et al.). Index.
£147.56
John Wiley & Sons Inc Posteriori Error Estimation Pure and Applied
Book SynopsisA posteriori error estimators have been intensely studied in recent years, owing to their remarkable capacity to enhance both speed and accuracy in computing. By effectively estimating error, the door has been opened for the possibility of controlling the entire computational process through new adaptive algorithms.Table of ContentsPreface xiii Acknowledgments xvii 1 Introduction 1 1.1 A Posteriori Error Estimation: The Setting 1 1.2 Status and Scope 2 1.3 Finite Element Nomenclature 4 1.3.1 Sobolev Spaces 5 1.3.2 Inverse Estimates 7 1.3.3 Finite Element Partitions 9 1.3.4 Finite Element Spaces on Triangles 10 1.3.5 Finite Element Spaces on Quadrilaterals 11 1.3.6 Properties of Lagrange Basis Functions 12 1.3.7 Finite Element Interpolation 12 1.3.8 Patches of Elements 13 1.3.9 Regularized Approximation Operators 14 1.4 Model Problem 15 1.5 Properties of A Posteriori Error Estimators 16 1.6 Bibliographical Remarks 18 2 Explicit A Posteriori Estimators 19 2.1 Introduction 19 2.2 A Simple A Posteriori Error Estimate 20 2.3 Efficiency of Estimator 23 2.3.1 Bubble Functions 23 2.3.2 Bounds on the Residuals 28 2.3.3 Proof of Two-Sided Bounds on the Error 31 2.4 A Simple Explicit Least Squares Error Estimator 32 2.5 Estimates for the Pointwise Error 34 2.5.1 Regularized Point Load 35 2.5.2 Regularized Green's Function 38 2.5.3 Two-Sided Bounds on the Pointwise Error 39 2.6 Bibliographical Remarks 4% 3 Implicit A Posteriori Estimators 43 3.1 Introduction 43 3.2 The Subdomain Residual Method 44 3.2.1 Formulation of Subdomain Residual Problem 45 3.2.2 Preliminaries 46 3.2.3 Equivalence of Estimator ^7 3.2.4 Treatment of Residual Problems 49 3.3 The Element Residual Method 50 3.3.1 Formulation of Local Residual Problem 50 3.3.2 Solvability of the Local Problems 52 3.3.3 The Classical Element Residual Method 54 3.3.4 Relationship with Explicit Error Estimators 54 3.3.5 Efficiency and Reliability of the Estimator 55 3.4 The Influence and Selection of Subspaces 56 3.4.1 Exact Solution of Element Residual Problem 56 3.4.2 Analysis and Selection of Approximate Subspaces 59 3.4.3 Conclusions 62 3.5 Bibliographical Remarks 63 4 Recovery-Based Error Estimators 65 4.1 Examples of Recovery-Based Estimators 66 4.1.1 An Error Estimator for a Model Problem in One Dimension 61 4.1.2 An Error Estimator for Bilinear Finite Element Approximation 69 4.2 Recovery Operators 72 4.2.1 Approximation Properties of Recovery Operators 73 4.3 The Superconvergence Property 75 4.4 Application to A Posteriori Error Estimation 76 4.5 Construction of Recovery Operators 77 4.6 The Zienkiewicz-Zhu Patch Recovery Technique 79 4.6.1 Linear Approximation on Triangular Elements 79 4.6.2 Quadratic Approximation on Triangular Elements 81 4.6.3 Patch Recovery for Quadrilateral Elements 82 4.7 A Cautionary Tale 82 4.8 Bibliographical Remarks 83 5 Estimators, Indicators, and Hierarchic Bases 85 5.1 Introduction 85 5.2 Saturation Assumption 88 5.3 Analysis of Estimator 89 5.4 Error Estimation Using a Reduced Subspace 90 5.5 The Strengthened Cauchy-Schwarz Inequality 94 5.6 Examples 98 5.7 Multilevel Error Indicators 100 5.8 Bibliographical Remarks 109 6 The Equilibrated Residual Method 111 6.1 Introduction 111 6.2 The Equilibrated Residual Method 112 6.3 The Equilibrated Flux Conditions 116 6.4 Equilibrated Fluxes on Regular Partitions 117 6.4.1 First-Order Equilibration Condition 118 6.4.2 The Form of the Boundary Fluxes 118 6.4.3 Equilibration Conditions in Terms of the Moments 120 6.4.4 Local Patch Problems for the Flux Moments 120 6.4.5 Procedure for Resolution of Patch Problems 123 6.4.6 Summary 127 6.5 Efficiency of the Estimator 128 6.5.1 Stability of the Equilibrated Fluxes 128 6.5.2 Proof of Efficiency of the Estimator 131 6.6 Equilibrated Fluxes on Partitions Containing Hanging Nodes 133 6.6.1 First-Order Equilibration 133 6.6.2 Flux Moments for Unconstrained Nodes 134 6.6.3 Flux Moments with Respect to Constrained Nodes 137 6.6.4 Recovery of Actual Fluxes 137 6.7 Equilibrated Fluxes for Higher-Order Elements 139 6.7.1 The Form of the Boundary Fluxes 141 6.7.2 Determination of the Flux Moments 141 6.8 Bibliographical Remarks 143 7 Methodology for the Comparison of Estimators 145 7.1 Introduction 145 7.2 Overview of the Technique 146 7.3 Approximation over an Interior Subdomain 149 7.3.1 Translation Invariant Meshes 149 7.3.2 Lower Bounds on the Error 152 7.3.3 Interior Estimates 153 7.4 Asymptotic Finite Element Approximation 157 7.4.1 Periodic Finite Element Projection on Reference Cell 157 7.4.2 Periodic Finite Element Projection on a Physical Cell 158 7.4.3 Periodic Extension on a Subdomain 159 7.4.4 Asymptotic Finite Element Approximation 160 7.5 Stability of Estimators 165 7.5.1 Verification of Stability Condition for Explicit Estimator 166 7.5.2 Verification of Stability Condition for Implicit Estimators 168 7.5.3 Verification of Stability Condition for Recovery-Based Estimator 169 7.5.4 Elementary Consequences of the Stability Condition 170 7.5.5 Evaluation of Effectivity Index in the Asymptotic Limit 172 7.6 An Application of the Theory 174 7.6.1 Computation of Asymptotic Finite Element Solution 174 7.6.2 Evaluation of the Error in Asymptotic Finite Element Approximation 178 7.6.3 Computation of Limits on the Asymptotic Effectivity Index for Zienkiewicz-Zhu Patch Recovery Estimator 180 7.6.4 Application to Equilibrated Residual Method 184 7.6.5 Application to Implicit Element Residual Method 184 7.7 Bibliographical Remarks 187 8 Estimation of the Errors in Quantities of Interest 189 8.1 Introduction 189 8.2 Estimates for the Error in Quantities of Interest 191 8.3 Upper and Lower Bounds on the Errors 193 8.4 Goal-Oriented Adaptive Refinement 197 8.5 Example of Goal-Oriented Adaptivity 198 8.5.1 Adaptivity Based on Control of Global Error in Energy 198 8.5.2 Goal-Oriented Adaptivity Based on Pointwise Quantities of Interest 198 8.6 Local and Pollution Errors 202 8.7 Bibliographical Remarks 205 9 Some Extensions 207 9.1 Introduction 207 9.2 Stokes and Oseen's Equations 208 9.2.1 A Posteriori Error Analysis 211 9.2.2 Summary 218 9.3 Incompressible Navier-Stokes Equations 219 9.4 Extensions to Nonlinear Problems 222 9.4.1 A Class of Nonlinear Problems 222 9.4.2 A Posteriori Error Estimation 224 9.4.3 Estimation of the Residual 225 9.5 Bibliographical Remarks 227 References 229 Index 239
£152.06
John Wiley & Sons Inc Fourier Series and Optical Transform Techniques
Book SynopsisFourier Series and Optical Transform Techniques in ContemporaryOptics An Introduction For anyone new to Fourier methods, this remarkable book willilluminate the subject like no other currently available. With over280 illustrations generated by computer graphics, it depicts in3-space (rather than the usual 2-space) the many basic functions ofoptical diffraction and imaging. These mind-stretchingvisualizations give the reader an enhanced understanding of bothFourier transform techniques and key principles in optics. At thesame time, the author provides a lucid text that covers wavenotation, the Fourier analysis of signals, the processing of lightin diffraction phenomena and imaging, Zernicke polynomials, Fouriertransforms for Fresnel diffraction, laser beacon adaptive optics,and related topics. Ideal for self-teaching, this book is highly recommended forworking engineers, technical staff, students of physical optics andsignal analysis, and Fourier novices in alTable of ContentsPartial table of contents: Some of the How and Why of Fourier Analysis. Fourier Series and Spectra in One-Dimension for Functions of FinitePeriod. Fourier Series and Spectra for Functions of Infinite Period; One Dimensional. Fourier Spectra for Non-Periodic Functions; One-Dimensional. The Diffraction of Light and Fourier Transforms in TwoDimensions. A Brief Summary of Linear Systems Theory Applied to OpticalImaging. Fourier Optical Transformations by Computer. Apodization and Super-Resolution, Phase from Shift, and MultipleApertures. Complex Apertures. Operations in the Fourier Transform Plane. Other Interesting and Related Topics. References. A Selected Bibliography. Index.
£155.66
John Wiley & Sons Inc Principles of Adsorption and Reaction on Solid
Book SynopsisTreats the important area of surface chemistry - or what happens on a molecular level when one substance comes in contact with another. Provides an understanding of the principles which govern adsorption and reactions of gases on solid surfaces. Describes what occurs and why processes happen the way they do, including discussions of applications.Table of ContentsThe Structure of Solid Surfaces and Adsorbate Overlayers. Adsorption I: The Binding of Molecules to Surfaces. Adsorption II: Adsorption Isotherms. Adsorption III: Kinetics of Adsorption. Introduction to Surface Reactions. Rate Laws for Reactions on Surfaces I: Kinetic Models. A Review of Reaction-Rate Theory. Models of Potential Energy Surfaces: Reactions as Curve Crossings and Electron Transfer Processes. Rates and Mechanisms of Surface Reactions. Index.
£209.66
John Wiley & Sons Inc Introduction to Discrete Dynamical Systems
Book SynopsisThis book introduces the reader to the fundamental principles, definitions, and results of dynamical systems and chaos. Rather than relegating chaos to the last chapter in the book, as is usually the case, this work treats chaos as an integral part of dynamical systems theory.Trade Review"From the preface: 'The purpose of this book is to present the fundamental ideas on discrete dynamical systems and chaos at the level of those undergraduates...who have completed the standard calculus sequence, with the inclusion of functions of several variables and linear algebra.'" (Mathematical Reviews, Issue 2001k)Table of ContentsDiscrete Dynamical Systems. One-Dimensional Dynamical Systems. R¯q, Matrices, and Functions. Discrete Linear Dynamical Systems. Nonlinear Dynamical Systems. Chaotic Behavior. Analysis of Four Dynamical Systems. Appendices. Index.
£155.66
John Wiley & Sons Inc Numerical Solution of Partial Differential
Book SynopsisFrom the reviews of Numerical Solution of Partial Differential Equations in Science and Engineering: The book by Lapidus and Pinder is a very comprehensive, even exhaustive, survey of the subject . . . [It] is unique in that it covers equally finite difference and finite element methods. Burrelle''s The authors have selected an elementary (but not simplistic) mode of presentation. Many different computational schemes are described in great detail . . . Numerous practical examples and applications are described from beginning to the end, often with calculated results given. Mathematics of Computing This volume . . . devotes its considerable number of pages to lucid developments of the methods [for solving partial differential equations] . . . the writing is very polished and I found it a pleasure to read! Mathematics of Computation Of related interest . . . NUMERICAL ANALYSTable of ContentsFundamental Concepts. Basic Concepts in the Finite Difference and Finite Element Methods. Finite Elements on Irregular Subspaces. Parabolic Partial Differential Equations. Elliptic Partial Differential Equations. Hyperbolic Partial Differential Equations. Index.
£144.85
John Wiley & Sons Inc Statistical Methods for the Analysis of
Book SynopsisIncludes a chapter on multiple linear regression in biomedical research, with sections containing the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.Trade Review"…useful in a course in biostatistics." (Journal of Statistical Computation and Simulation, September 2005) "...a nice overview of statistical topics...an excellent book to have...highly recommend this book for students and researchers..." (Statistical Methods in Medical Research, Vol 13, 2004) "…interesting and useful…I recommend it as an addition to your statistical library, and if you already own the first edition, it would be worthwhile to update it." (The American Statistician, Vol. 58, No. 2, May 2004)Table of ContentsDedication v Preface to the 1987 Edition xvii Preface to the 2002 Edition xxi Acknowledgment xxiii 1 Introduction 1 2 Descriptive Statistics 9 3 Basic Probability Concepts 49 4 Further Aspects of Probability 79 5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications 119 6 Comparison of Two Groups: t-Tests and Rank Tests Introduction 151 7 Comparison of Two Groups: Chi-Square and Related Procedures 217 8 Tests of Independence and Measures of Association for Two Random Variables 263 9 Least-Squares Regression Methods: Predicting One Variable from Another 307 10 Comparing More than Two Groups Observations: Analysis of Variance for Comparing Groups 359 11 Comparing More than Two Groups of Observations: Rank Analysis of Variance for Group Comparisons 417 12 Comparing More than Two Groups of Observations: Chi-Square and Related Procedures 441 13 Special Topics in Analysis of Epidemiologic and Clinical Data: Studying Association between a Disease and a Characteristic 461 14 Estimation and Comparison of Survival Curves 509 15 Multiple Linear Regression Methods: Predicting One Variable from Two or More Other Variables 541 Appendix 623 Topic Index 673
£154.76
John Wiley & Sons Inc Dynamic Systems 3e
Book SynopsisThe book presents the methodology applicable to the modeling and analysis of a variety of dynamic systems, regardless of their physical origin. It includes detailed modeling of mechanical, electrical, electro-mechanical, thermal, and fluid systems.Table of ContentsIntroduction. Translational Mechanical Systems. Standard Forms for System Models. Block Diagrams and Computer Simulation. Rotational Mechanical Systems. Electrical Systems. Transform Solutions of Linear Models. Transform Function Analysis. Developing a Linear Model. Electromechanical Systems. Thermal Systems. Fluid Systems. Block Diagrams for Dynamic Systems. Modeling, Analysis, and Design Tools. Feedback Design with MATLAB. Appendix A: Units. Appendix B: Matrices. Appendix C: Complex Algebra. Appendix D: Classical Solution of Differential Equations. Appendix E: Laplace Transforms. Appendix F: Selected Reading. Appendix G: Answers to Selected Problems. Index.
£230.36
John Wiley & Sons Inc Modern Advanced Mathematics for Engineers
Book SynopsisMost disciplines in electrical and computer engineering require a working knowledge of relatively sophisticated mathematical concepts. This book presents those mathematical concepts and methods essential for professionals and students working in electrical or computer engineering.Trade Review"The appearance of the book is pleasing and it readswell..." (The Mathematical Gazette, Nov 2002) "From the preface: 'This book is written with the aim ofproviding students with a strong foundation in modern appliedmathematics.'" (Mathematical Reviews, 2001 I) "...a useful account of basic ideas." (Mathematika,No.48, 2001) "One should be grateful to the authors for having done a goodjob" (Zentrablatt Math, Vol.979, No.04, 2002) "...textbook for a one-semester graduate course providingengineering students with a foundation in modern appliedmathematics." (SciTech Book News, Vol. 26, No. 2, June2002)Table of ContentsDedication. Preface. The Basic of Set Theory. Relations and Mappings. Mathematical Logic. Algebraic Structures: Group Through Linear Space. Linear Mappings and Matrices. Metrics and Topological Properties. Banach and Hilbert Spaces. Orthonormal Bases and Fourier Series. Operator Equations. Fourier and Laplace Transforms. Partial Differential Equations. Topic Index.
£145.76
John Wiley & Sons Inc Understanding Calculus
Book SynopsisGives you what you need to know - basic essential concepts - about calculus. Suitable for those looking for a readable alternative to the usual unwieldy calculus text, this title provides in a condensed format the material covered in the standard two-year calculus course. It also covers vectors, lines, and planes in space; and line integrals.Trade Review"...expands coverage to vectors and calculus of several variables...plenty of worked out problems..." (American Mathematical Monthly, August/September 2003) "...material included is well formulated and approachable...recommended." (Choice, Vol. 41, No. 1, September 2003)Table of ContentsAUTHOR'S MESSAGE TO THE READER vii ANNOTATED TABLE OF CONTENTS ix ACKNOWLEDGMENTS xv CHAPTER 1 Lines 1 CHAPTER 2 Parabolas, Ellipses, Hyperbolas 7 CHAPTER 3 Differentiation 13 CHAPTER 4 Differentiation Formulas 19 CHAPTER 5 The Chain Rule 25 CHAPTER 6 Trigonometric Functions 31 CHAPTER 7 Exponential Functions and Logarithms 39 CHAPTER 8 Inverse Functions 45 CHAPTER 9 Derivatives and Graphs 51 CHAPTER 10 Following the Tangent Line 57 CHAPTER 11 The Indefinite Integral 63 CHAPTER 12 The Definite Integral 69 CHAPTER 13 Work, Volume, and Force 75 CHAPTER 14 Parametric Equations 81 CHAPTER 15 Change of Variable 87 CHAPTER 16 Integrating Rational Functions 91 CHAPTER 17 Integration By Parts 97 CHAPTER 18 Trigonometric Integrals 101 CHAPTER 19 Trigonometric Substitution 107 CHAPTER 20 Numerical Integration 115 CHAPTER 21 Limits At oo; Sequences 119 CHAPTER 22 Improper Integrals 127 CHAPTER 23 Series 133 CHAPTER 24 Power Series 141 CHAPTER 25 Taylor Polynomials 149 CHAPTER 26 Taylor Series 155 CHAPTER 27 Separable Differential Equations 161 CHAPTER 28 First-Order Linear Equations 167 CHAPTER 29 Homogeneous Second-Order Linear Equations 173 CHAPTER 30 Nonhomogeneous Second-Order Equations 179 CHAPTER 31 Vectors 185 CHAPTER 32 The Dot Product 195 CHAPTER 33 Lines and Planes in Space 201 CHAPTER 34 Surfaces 211 CHAPTER 35 Partial Derivatives 217 CHAPTER 36 Tangent Plane and Differential Approximation CHAPTER 37 Chain Rules 227 CHAPTER 38 Gradient and Directional Derivatives 233 CHAPTER 39 Maxima and Minima 239 CHAPTER 40 Double Integrals 245 CHAPTER 41 Line Integrals 255 CHAPTER 42 Green's Theorem 259 CHAPTER 43 Exact Differentials 267 ANSWERS 273 INDEX 299 ABOUT THE AUTHOR 303
£94.46
John Wiley & Sons Inc Optimization Principles
Book SynopsisToday''s need-to-know optimization techniques, at your fingertips The use of optimization methods is familiar territory to academicians and researchers. Yet, in today''s world of deregulated electricity markets, it''s just as important for electric power professionals to have a solid grasp of these increasingly relied upon techniques. Making those techniques readily accessible is the hallmark of Optimization Principles: Practical Applications to the Operation and Markets of the Electric Power Industry. With deregulation, market rules and economic principles dictate that commodities be priced at the marginal value of their production. As a result, it''s necessary to work with ever-more-sophisticated algorithms using optimization techniques-either for the optimal dispatch of the system itself, or for pricing commodities and the settlement of markets. Succeeding in this new environment takes a good understanding of methods that involve linear and nonTrade Review"...an important contribution to the field of power system analysis...should provide the reader with a pleasant learning experience." (IEEE Power & Energy Magazine, November/December 2005)Table of ContentsPreface. 1. Introduction. PART I: MATHEMATICAL BACKGROUND. 2. Fundamentals of Matrix Algebra. PART II: LINEAR OPTIMIZATION. 3. Solution of Equations, Inequalities, and Linear Programs. 4. Solved Linear Program Problems. PART III: NONLINEAR OPTIMIZATION. 5. Mathematical Background to Nonlinear Programs. 6. Unconstrained Nonlinear Optimization. 7. Constrained Nonlinear Optimization. 8. Solved Nonlinear Optimization Problems. Appendix A: Basic Principles of Electricity. Appendix B: Network Equations. Appendix C: Relation Between Pseudo-Inverse and Least-Square Error Fit. Bibliography. Index. About the Author.
£121.46
John Wiley & Sons Inc Applied Bayesian Modelling Wiley Series in
Book SynopsisBayesian statistics uses information from past experience to infer the results of future events. With recent advances in computing power and the development of computer intensive methods for statistical estimation, Bayesian approaches to model estimation have become more feasible and popular.Trade Review"I recommend…highly to statisticians, [and] health researchers...among others to consider keeping on their bookshelf." (Journal of Statistical Computation and Simulation, April 2005) "…a great book…fills a critical gap in existing literature. It is an excellent book for anyone interested in Bayesian modeling…" (Journal of the American Statistical Association, March 2005) "It is certainly a fine choice as a supporting reference in either a first or second Bayesian methods course…” (Technometrics, May 2004) "...has a contemporary feel, with recent developments in financial time series modelling and epidemiology included..." (Short Book Reviews, Vol 23(3), December 2003)Table of ContentsPreface. The Basis for, and Advantages of, Bayesian Model Estimation via Repeated Sampling. Hierarchical Mixture Models. Regression Models. Analysis of Multi-Level Data. Models for Time Series. Analysis of Panel Data. Models for Spatial Outcomes and Geographical Association. Structural Equation and Latent Variable Models. Survival and Event History Models. Modelling and Establishing Causal Relations: Epidemiological Methods and Models. Index.
£95.36
Wiley-Blackwell Robust Regression and Outlier Detection
Book SynopsisThis comprehensive book provides readers with an applications--oriented introduction to robust regression and outlier detection - emphasising A"high--breakdownA" methods which can cope with a sizeable fraction of contamination. Its self--contained treatment allows readers to skip the mathematical material, which is concentrated in a few sections.Trade Review"…a wonderful book about methods of identifying outliers and then developing robust regression." (Journal of Statistical Computation and Simulation, July 2005)Table of Contents1. Introduction. 2. Simple Regression. 3. Multiple Regression. 4. The Special Case of One-Dimensional Location. 5. Algorithms. 6. Outlier Diagnostics. 7. Related Statistical Techniques. References. Table of Data Sets. Index.
£124.15
John Wiley & Sons Inc The Elements of Stochastic Processes with
Book SynopsisDevelops an introductory and relatively simple account of the theory and application of the evolutionary type of stochastic process. Professor Bailey adopts the heuristic approach of applied mathematics and develops both theoretical principles and applied techniques simultaneously.Table of ContentsGenerating Functions. Recurrent Events. Random Walk Models. Markov Chains. Discrete Branching Processes. Markov Processes in Continuous Time. Homogeneous Birth and Death Processes. Some Non-Homogeneous Processes. Multi-Dimensional Processes. Queueing Processes. Epidemic Processes. Competition and Predation. Diffusion Processes. Approximations to Stochastic Processes. Some Non-Markovian Processes. References. Solutions to Problems. Indices.
£174.56
John Wiley & Sons Inc Engineering Applications of Correlation and
Book SynopsisExpanded to cover more advanced applications where statistical properties of data can be nonstationary and the physical systems nonlinear as opposed to only linear. Stresses the practical use and interpretation of analyzed data to solve problems. Special attention is given to bias and random errors involved in desired estimates and the proper interpretation of results from specific applications. Includes numerous case studies concerned with dynamic problems which can occur in a variety of fields.Table of ContentsProbability Functions and Amplitude Measures. Correlation and Spectral Density Functions. Single-Input/Single-Output Relationships. System Identification and Response. Propagation-Path Identification. Single-Input/Multiple-Output Problems. Multiple-Input/Multiple-Output Relationships. Energy-Source Identification. Procedures to Solve Multiple-Input/Multiple-Output Problems. Statistical Errors in Estimates. Nonstationary Data Analysis Techniques. Nonlinear System Analysis Techniques. References. List of Figures. List of Tables. Index. Glossary of Symbols.
£197.06
John Wiley & Sons Inc Planning of Experiments
Book SynopsisOriginally published in 1958, this text offers a simple analysis of the principles of experimental design. Emphasis is placed on basic concepts rather than the calculation of technical details. It is possible to use the book in conjunction with a text on statistical analysis.Table of ContentsPreliminaries. Some Key Assumptions. Designs for the Reduction of Error. Use of Supplementary Observations to Reduce Error. Randomization. Basic Ideas About Factorial Experiments. Design of Simple Factorial Experiments. Choice of Number of Observations. Choice of Units, Treatments, and Observations. More About Latin Squares. Incomplete Nonfactorial Designs. Fractional Replication and Confounding. Cross-Over Designs. Some Special Problems. General Bibliography. Appendix. Indexes.
£116.06
John Wiley & Sons Inc Applied Numerical Methods for Engineers
Book SynopsisWritten for engineering students, this textbook on numerical methods stresses the typical methods that engineers use in daily practice. A chapter on design introduces problems which bring relevance to the use of this tool in engineering situations.Table of ContentsFOUNDATIONS. Systems of Linear Algebraic Equations. Nonlinear Algebraic Equations. DATA ANALYSIS. Statistics and Least-Squares Approximation. Curve Fitting. NUMERICAL CALCULUS. Differentiation and Integration. Ordinary Differential Equations. ADVANCED TOPICS. Matrix Eigenproblems. Introduction to Partial Differential Equations. Design and Optimization. Appendices. References. Bibliography. Answers to Selected Problems. Index.
£198.86
John Wiley & Sons Inc The Boundary Element Method Applications in
Book SynopsisProvides a comprehensive presentation of the boundary element method (BEM) from fundamentals to advanced engineering applications and encompasses: Steady and transient heat transfer; Potential and viscous fluid flows; Frequency and time-domain acoustics; and Corrosion and other electrochemical problems.Table of ContentsPreface Preface to Volume 1 Acknowledgements Introduction Potential Problems Steady Heat Transfer Transient Heat Transfer Acoustics Electrochemical Problems Flow of Ideal Fluids Slow Viscous Flow General Viscous Flow Inverse Problems Numerical Integration Index
£181.76
John Wiley & Sons Inc The Site Calculations Pocket Reference
Book SynopsisThe revised field companion for construction, recreation department, and landscape professionals Put it in your pocket and go! For the busy professional working on-site--this updated, handy pocket reference puts all the formulas and calculations you need at your fingertips. Now with a convenient, lay-flat comb binding, this book is invaluable for all areas of general site construction. It gives you fast access to the information you want--when you want it--complete with real-world examples. This revised Second Edition features a new chapter on sports fields that includes descriptions and schematics for more than forty different fields. It also provides the latest information on: * Earthworks and materials * Drainage, sewers, and irrigation * Grassing, landscaping, and ground covers * Temperature, area, and time measurement * Units of weight and measure * Map and surveyor information * WorldwiTable of ContentsSection 1 Earthworks and Materials. 1.1 Soils—Angles of Repose 2 1.2 Volume of Sand or Gravel in a Stockpile 2 1.3 Approximate Swelling Factors for Various Soil Types 3 1.4 Approximate Shrinkage Factors for Various Soil Types 3 1.5 Soil Permeability 3 1.6 Water Retention for Various Soils 4 1.7 Weights of Materials 4 1.8 Water-Holding Estimates of a Variety of Soils 5 1.9 Triangle of Physical Characteristics of Various Soils 6 1.10 Estimated Runoff Volume from a 24-Hour, 7-Inch Rain Event 6 1.11 Average Soil Infiltration Rates for Various Soils by Percent of Slope 7 1.12 Computation for Volume of Excavated Material (English) 7 1.13 Computation for Volume of Excavated Material (Metric) 8 1.14 Computation of Materials Volume from Trench Excavation (English) 9 1.15 Computation of Materials Volume from Trench Excavation (Metric) 9 1.16 Angles of Slopes 10 1.17 Slope Measurement Plan (Horizontal) to True Measure 10 1.18 Approximate Equivalencies: Slope/Grade/Degree 11 1.19 Safe Limit Restrictions (General Guide) 11 1.20 Soil Coverage 12 1.21 Top Dressing (English) 13 1.22 Top Dressing (Metric) 13 1.23 Practical Examples of Specialized Small Areas of Fill (Sand Trap) 14 1.24 Calculation of Area of an Odd-Shaped Area 15 1.25 Calculation of Fill Materials for an Odd-Shaped Area (Golf Green) 16 1.26 Chart of Volumes by Area 17 Section 2 Drainage 2.1 Manning’s “n” Value for Design 20 2.2 Circular Pipe Flow Capacity (Double Wall—Smooth) 21 2.3 Circular Pipe Flow Capacity (Single Wall—Spiral). 2.4 Pipe Size Conversion (Drainage) English to Metric 23 2.5 Example of Circular Pipe Flow Capacity Calculation 23 2.6 Diagram for Pipe Flow Capacity Calculation 24 2.7 Drainage Calculation: Water Quantity by Area 25 2.8 Pipe Conversion Factors (Natural Gas, Irrigation, Drainage, etc.) 26 Section 3 Irrigation,Water Supply, and Materials. 3.1 Pipe Data Introduction. 3.2 Lake Lining Calculation. 3.3 Pressure Loss from Friction per 100 Ft. of Pipe (Pounds per Square Inch). 3.4 Pressure Conversion Chart PSI-Kg/Cm-BAR. 3.5 Pipe Conversion Factors. 3.6 Velocity of Flow (Feet per Second). 3.7 Surge Pressures and Water Hammer. 3.8 Comparative Flow Capacities for Pipe. 3.9 Uniformity and Efficiency. 3.10 Uniformity Coefficient. 3.11 System Distribution Uniformity. 3.12 Efficiencies. 3.13 Designing Irrigation System Capabilities. 3.14 The Soil Reservoir. 3.15 Natural Water Loss. 3.16 Guides to Determining ET Rate. 3.17 Minimizing System Losses. 3.18 Other Considerations. 3.19 Irrigation Water Requirements. 3.20 Scheduling Procedures. 3.21 Summary. 3.22 Sprinkler Spacing. 3.23 Precipitation Rate Formulas. 3.24 Sprinkler Efficiency and Spacing under Certain Conditions. 3.25 Approximate Number of Sprinklers per Acre. 3.26 Example—How to Determine Pipe Size per Requirement. 3.27 Pump Definitions. 3.28 Practical Suction Lifts at Various Elevations. 3.29 Pump Cost and Efficiency Data. 3.30 Cost of Pumping Water per 1,000 U.S. Gallons Pumped. 3.31 Cost per Hour of Pumping under Continuous Conditions. 3.32 Formula for Figuring Efficiency of Pump. 3.33 Formula for Determining Pump Horsepower. 3.34 Pump Calculation: Size for Duty. 3.35 Miscellaneous Irrigation Data. 3.36 Example— Irrigation System Design for Sports Fields. 3.37 Materials for Sprinkler Systems. 3.38 Maintenance Procedure for Irrigation System. 3.39 Winterization in Southern Climates. 3.40 Winterization in Northern Climates. 3.41 Spring Start-Up. 3.42 Electrical Table for Single-Phase Irrigation Wiring. 3.43 Electrical Table for Basic Three-Phase Irrigation Wiring. 3.44 Voltage Loss for Various Wire Sizes per 100 Ft. of Copper Wire. 3.45 Wire Sizing Calculation Form. 3.46 American to Metric Cable Size Conversion. Section 4 Concrete, Retaining Walls, Streets, and Weir Structures. 4.1 Approximate Weights of Materials Required per Cubic Yard of Concrete. 4.2 Approximate Weights of Materials Required per Cubic Yard of Concrete. 4.3 Approximate Weights of Materials Required per Cubic Yard of Concrete. 4.4 Approximate Weights of Materials Required per Cubic Yard of Concrete. 4.5 Quantities of Portland Cement for Concrete. 4.6 Materials for Concrete per Cubic Yard. 4.7 Quantities: Concrete for Footings. 4.8 Concrete Surface Coverage per Cubic Yard. 4.9 Reinforcing Steel Requirements for Concrete. 4.10 Concrete Mixer—Average Output in Cubic Yards per Hour. 4.11 Properties of Plywood Forming. 4.12 Allowable Stresses for Formwork Lumber. 4.13 Approximate Board Foot Content of Sawed Railroad Ties. 4.14 Calculations for Retaining Walls— Cubic Yards per Area by Depth. 4.15 Recommended Guidelines for Subdivision or City Street Construction. 4.16 Typical Road Section Sketch. 4.17 Discharge from Rectangular Notch Weirs with End Contractions. 4.18 Discharge from Triangular Notch Weirs with End Contractions. Section 5 Grassing, Landscaping, Fertilization, and Ground Covers. 5.1 Turfgrasses Stolonization—What is a Bushel? 5.2 What Does “Certified” Mean? 5.3 Ornamental Grasses. 5.4 Recommended Seeding Rates of Some Grasses. 5.5 Characteristics of Some Turfgrasses. 5.6 Coverage Area per Bale of Bean Straw. 5.7 Grass Stolons: Distribution Rate by Means of Sprigging. 5.8 Grass Stolons: Quantities Required for Broadcast Distribution. 5.9 Coverage Areas for Turf and Other Ground Covers via Plugs. 5.10 Fertilization (Nitrogen Requirements). 5.11 Coverage Area per Flat of Ground Covers Square Feet per Flat. 5.12 Liners and Hedge Plants: Plants Required per 100 Lin. Ft. 5.13 Plants Required per 100 SF: Various Spacings. 5.14 Flats of Plants Required per 100 SF: Various Spacings and Various Quantities per Flat. 5.15 Number of Shrubs or Plants for an Acre at Various Spacings. 5.16 Peat Moss Coverage: Depth in Inches per Square Surface Footage. 5.17 Steer Manure Coverage: Depth in Inches per Square Surface Footage. 5.18 Steer Manure: Rates per Acre Based on Required Rates per 1,000 SF. 5.19 Nursery Container Stock: Approximate Backfill Volume for Various Container Stock: Round Plant Pits, Vertical Sides. 5.20 Nursery Container Stock: Volume of Excavated Soil Resulting from Multiple Plantings: Square Planting Pits. 5.21 Nursery Container Stock: Approximate Backfill Volume for Various Container Stock Square Plant Pits, Vertical Sides. 5.22 Nursery Container Stock. 5.23 Tree Pit Excavation for Nursery Container Stock Square Pits, Vertical Sides. 5.24 Tree Pit Excavation for Nursery Container Stock Round Pits, Vertical Sides. 5.25 Nursery Container Stock: Volume of Excavated Soil Resulting from Multiple Plantings: Round Plant Pits. 5.26 Suggested Planting Distances for Some Fruit Trees. 5.27 Tree Cabling Material Combinations. 5.28 Hydroseeders: Area Coverage per Load. 5.29 Hydroseeder Coverage Using Seed, Fertilizer, and Mulch. 5.30 Hydroseeder Coverage Using Seed and Fertilizer Only. 5.31 Usage Rates for a Combination of Organic and Synthetic Products. 5.32 Usage Rates for Synthetic Fiber Bond. 5.33 Usage Rates for Gum-Based Organic Tackifier. 5.34 Seed Facts for Native Prairie Grasses and Legumes: Cool Season. 5.35 Seed Facts for Native Prairie Grasses and Legumes: Warm Season. 5.36 Seed Facts for Legumes. 5.37 Seed Facts for Cool-Season Turfgrasses. 5.38 Seed Facts for Warm-Season Foragegrasses. 5.39 Plant Hardiness Zones. 5.40 USDA Plant Hardiness Zone Map. 5.41 Shade and Ornamental Trees. 5.42 Ornamental Shrubs. 5.43 Fruit Trees. 5.44 Nut Trees. 5.45 Conifers. 5.46 Broadleaves. Section 6 Sports Fields. 6.1 Field Spaces. 6.2 Tolerances for Selecting the Best Turfgrass for Your Needs (Cool and Warm Season). 6.3 Types of Field Turf. 6.4 Lighting. 6.5 Drainage. 6.6 Irrigation. 6.7 Sports Field Space Requirements (General). 6.8 Archery. 6.9 Athletics (Track and Field) Field Events. 6.10 Athletics (Track and Field) Track Events. 6.11 Badminton. 6.12 Baseball. 6.13 Basketball. 6.14 Indoor and Lawn Bowls and Boules (Bocce/Petanque). 6.15 Boxing (International). 6.16 Cricket (Outdoor and Indoor). 6.17 Croquet. 6.18 Equestrian. 6.19 Fencing. 6.20 Football (American-Canadian). 6.21 Football (Aussie Rules). 6.22 Football (Gaelic). 6.23 Football (Rugby League). 6.24 Football (Rugby Union). 6.25 Football (Association Soccer). 6.26 Handball. 6.27 Horseshoes. 6.28 Hockey (Field). 6.29 Hockey (Indoor). 6.30 Hurling (Men’s). 6.31 Lacrosse (Men’s). 6.32 Lacrosse (Women’s). 6.33 Netball. 6.34 Polo. 6.35 Shuffleboard. 6.36 Softball. 6.37 Squash Rackets. 6.38 Tennis (Paddle). 6.39 Tennis (Platform). 6.40 Tennis. 6.41 Volleyball. Section 7 General Information. 7.1 Temperature Conversion. 7.2 Angular and Circular Measure. 7.3 Measurement of Time. 7.4 Measurement of Time: Converting Minutes to Decimal Hours. 7.5 Converting Inches and Fractions to Decimal Parts of a Foot. 7.6 Decimal Equivalents Table. 7.7 Circumferences and Areas of Circles. 7.8 Units of Length. 7.9 Units of Area. 7.10 Units of Length (Metric). 7.11 Units of Area (Metric). 7.12 Square Tracts of Land (English). 7.13 Area Conversion: Square Feet to Equivalent Acreage. 7.14 Area Conversion: Acres to Equivalent Square Footage. 7.15 Converting Miles to Kilometers and Kilometers to Miles. 7.16 Converting Feet to Meters and Meters to Feet. 7.17 Converting Inches to Centimeters and Centimeters to Inches. 7.18 Measurement of Area Conversions: English System to Metric System. 7.19 Measurement of Area Conversions: Metric System to English System. 7.20 Measurement of Volume Conversions: English System to Metric System. 7.21 Units of Weight (Metric). 7.22 Units of Volume (English). 7.23 Units of Volume (English): Conversions. 7.24 Units of Cubic Measure (Metric). 7.25 Units of Weight (English). 7.26 Units of Weight Conversions: English System to Metric System. 7.27 Units of Volume (English): Conversions. 7.28 Units of Dry Measure. 7.29 Units of Dry Measure: Conversions. 7.30 Dry Materials: Conversion Use for Small Areas. 7.31 Units of Liquid Measure. 7.32 Units of Liquid Measure: Conversions. 7.33 Units of Liquid Measure (Metric). 7.34 Units of Liquid Measure: Weight Equivalents. 7.35 Units of Water Measurement and Equivalencies. 7.36 Units of Liquid Measure Equivalencies: Gallons/Pounds/Cubic Feet. 7.37 Capacity of Square Pools per Foot of Depth. 7.38 Capacity of Rectangular Pools per Foot of Depth. 7.39 Capacity of Round Pools per Foot of Depth. 7.40 Liquid Materials: Conversions for Use for Small Areas. 7.41 Volumes Based on Areas of Water by Depth (Cu./Yds.). 7.42 Calculation of Volume Based on Area of Water by Depth. 7.43 Conversion Table for U.S. and Metric Systems. 7.44 USGA Sand Specification. 7.45 Equipment Amortization Table. 7.46 Simple Interest Table. 7.47 30 Days Interest Table. 7.48 World Time Zone Map. Section 8 Formulas for Areas and Volumes of Various Geometric Figures. 8.1 Rectangle. 8.2 Parallelogram. 8.3 Trapezoid. 8.4 Rectangular Prism. 8.5 Any Prism. 8.6 Pyramid. 8.7 Right Triangle. 8.8 Any Triangle. 8.9 Regular Polygon. 8.10 Any Cylinder. 8.11 Any Cone and Frustum of Any Cone. 8.12 Ellipse. 8.13 Circle. 8.14 Sector of a Circle. 8.15 Segment of a Circle. Section 9 Map and Surveyor Information. 9.1 Scale Equivalents: Scale 1/16" to 1'. 9.2 Scale Equivalents: Scales 1" to 10'/1" to 80'. 9.3 Scale Equivalents: Scales 1"/100' to 1"/1,000'. 9.4 Scale Equivalents: Scales 1" = 50' to 1" = 10 miles. 9.5 Slope Stake. 9.6 Stadia Correction and Horizontal Distances. 9.7 Chains to Feet and Feet to Chains Conversions. 9.8 Trigonometric Formulas. 9.9 Reduction to Horizontal. 9.10 Natural Trigonometrical Functions. 9.11 Curve Table. 9.12 Tangents and Externals to a 1-Degree Curve. 9.13 Useful Relations. 9.14 Square Measure and Surveyor’s Measure. 9.15 Inches to Decimals of a Foot. 9.16 Minutes in Decimals of a Degree. 9.17 Middle Ordinates of Length of Rail (Feet). 9.18 Short Radius Curves. 9.19 Rods in Feet, Tenths, and Hundredths of Feet. 9.20 Links in Feet, Tenths, and Hundredths of Feet. 9.21 Inches in Decimals of a Foot. 9.22 Curve Formulas. 9.23 Table of Powers and Roots (1–100). 9.24 Square Roots and Cube Roots (1,000–2,000). Section 10 Sanitary Sewers. 10.1 Separation Distances. 10.2 Minimum Separation between Sanitary Facilities and Other Features. 10.3 Expected Hydraulic Loading Rates. 10.4 Intermittent Stream Effluent Limits. 10.5 Minimum Size of Sewer Appurtenances. 10.6 Recommended Hazen-Williams Coefficients for Sewer Pipe. 10.7 System Pressures and Pump Types. 10.8 Septic Tanks. 10.9 Estimating the Size Grease Trap for Restaurants and Hospitals. 10.10 Buried Filters. 10.11 Open Filters—Single Pass. 10.12 Filter Media. 10.13 Recommended Sewage Application Rates. 10.14 Site Criteria for Mounds. 10.15 Allowable Lateral Lengths (Ft.). 10.16 Sidewall Areas of Circular Seepage Pits. 10.17 Cascade Aeration. 10.18 Conversion Factors. 10.19 Mound Design Example. Section 11 Worldwide Weather Conditions. 11.1 Temperature Distribution. 11.2 Distribution of Precipitation. 11.3 North America. 11.4 South America. 11.5 Europe. 11.6 Asia. 11.7 Africa. 11.8 Australia. 11.9 Temperature Data for Representative Worldwide Stations. 11.10 Precipitation Data for Representative Worldwide Stations. 11.11 Worldwide Extremes of Temperature and Precipitation. Appendix Miscellaneous Conversion Factors. Index.
£59.36
John Wiley & Sons Inc Computational Molecular Biology An Introduction
Book SynopsisThis introductory level text is suitable for use by advanced undergraduate and graduate students of computational biology. Written by experienced authors, it provides detailed coverage of many algorithms, including applications and possible modifications.Trade Review"...much-needed introductory level text..." - La Doc Sti, July 2000Table of ContentsMolecular Biology. Math Primer. Sequence Alignment. All About Eve. Hidden Markov Models. Structure Prediction. Appendices. References. Index.
£231.26
John Wiley & Sons Inc Computational Molecular Biology
Book SynopsisRecently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and archiving. This requirement has given birth to the truly interdisciplinary field of computational biology, or bioinformatics, a subject reliant on both theoretical and practical contributions from statistics, mathematics, computer science and biology. * Provides the background mathematics required to understand why certain algorithms work * Guides the reader through probability theory, entropy and combinatorial optimization * In-depth coverage of molecular biology and protein structure prediction * Includes several less familiar algorithms such as DNA segmentation, quartet puzzling and DNA strand separation prediction * Includes class tested exercises useful for self-study * Source code of programs available on a Web site Primarily aimed at advanced undergradTrade Review"...much needed introductory level text on the subject..." (La Doc STI, July 2000) "...very concise and compact..." (Mathematical Reviews, 2002h)Table of ContentsMolecular Biology. Math Primer. Sequence Alignment. All About Eve. Hidden Markov Models. Structure Prediction. Appendices. References. Index.
£77.36
John Wiley & Sons Inc Mechanics 2e Wiley series in introductory
Book SynopsisMechanics Second Edition P. Smith Department of Mathematics University of Keele, UK and R.C. Smith Open University, UK A revised and updated edition of the authors' highly successful earlier book, this introductory text on Mechanics is designed to give a thorough grounding in particle dynamics and elementary rigid body dynamics.Table of ContentsVectors. Kinematics: Geometry of Motion. Principles of Mechanics. Applications in Particle Dynamics. Work and Energy. Variable Mass Problems: Rocket Motion. Mechanical Oscillations: Linear Theory. Orbits. Non-Linear Dynamics. Rotating Frames of Reference. Appendix. Answers and Comments on the Exercises. Further Reading. Index.
£68.35
Wiley Linear Multivariable Control
Book SynopsisDetails the basic theory of polynomial and fractional representation methods for algebraic analysis and synthesis of linear multivariable control systems. It also serves as a self-contained treatise of the mathematical theory so that results and techniques of the ``state space approaches'''' for regular and singular systems appear as special cases of a general theory covering the wider class of PMDs of linear systems. Among the topics covered are: real rational vector spaces and rational matrices, pole and zero structure of rational matrices at infinity, proper and omega stable rational fuctions and matrices.Table of ContentsReal Rational Vector Spaces and Rational Matrices. Polynomial Matrix Models of Linear Multivariable Systems. Pole and Zero Structure of Rational Matrices at Infinity. Dynamics of Polynomial Matrix Models. Proper and Omega-Stable Rational Functions and Matrices. Feedback System Stability and Stabilization. Some Algebraic Design Problems. Notations. Appendices. Index.
£151.16
John Wiley & Sons Inc Finite Element Modeling of Environmental Problems
Book SynopsisBecause of its ability to treat both regions with irregular boundaries and with different material types, the finite element method is increasingly being applied to surface water and soil transport problems and this is the focus of the present volume. The method is ideally suited to simulation of complex real applications for resolving environmental issues and for conducting environmental impact studies. The present volume focuses on the two main areas of environmental modeling with finite elements and the supporting finite element methodology. Five chapters are devoted to ocean and coastal engineering, one to other surface water problems, several to ground water modeling and contaminant transport, including radioactive waste, and the remainder to mathematical models, particularly for mixed finite elements and nonlinear problems. Environmental problems are of increasing topicality and importance today. Special care has been taken in organizing and editing the material to form the rightTable of ContentsPartial table of contents: Modeling Surface Water Flow (R. Walters). Environmental Hydrodynamics: Comprehensive Model for the Gulf ofMaine (D. Lynch, et al.). Surface Elevation and Circulation in Continental Margin Waters (J.Westerink, et al.). An Improved Finite Element Model for Shallow Water Problems (O.Zienkiewicz & P. Ortiz). An Entropy Variable Formulation and Petrov-Galerkin Method for theShallow Water Equations (S. Bova & G. Carey). Tidal Simulation Using Conjugate Gradient Methods (E. Barragy, etal.). 3D Finite Element Hydrodynamic Model (M. Andreola, et al.). Po River Delta Flow (V. Pennati & S. Corti). Circulation and Salinity Intrusion in Galveston Bay, Texas (R.Berger). Sentinels and Parameter Indentification (T. Mannikko). Contaminant Transport with Nonlinear, Nonequilibrium AdsorptionKinetics (C. Dawson). Substructure Preconditioning for Porous Flow Problems (R. Ewing, etal.). Error Estimates for Saturated Groundwater Flows (S. Chow). Waste Encapsulation by In Situ Vitrification (R. McLay, etal.). Index.
£305.96
John Wiley & Sons Inc Analysis of Variance for Sensory Data
Book SynopsisAnalysis of variance (ANOVA) is a statistical technique used in a number of chemical areas including the food industry. This handbook presents a guide to the uses of the technique of ANOVA applied to sensory analysis. It stresses the practical implications of the topic.Table of ContentsFactorial Designs. Further Aspects of Design and Modelling. Analysis of Variance. Random or Fixed Assessors in Analysis of Variance. More Complex ANOVA Situations. Replicates in Sensory Analysis. Multiple Comparisons. Two Detailed Examples. References and Relevant Literature. Appendices. Index.
£124.15
John Wiley & Sons Inc Wavelets
Book SynopsisWith applications in pattern recognition, data compression and numerical analysis, the wavelet transform is a key area of modern mathematics that brings new approaches to the analysis and synthesis of signals. This book presents the central issues and emphasizes comparison, assessment and how to combine method and application. It reviews different approaches to guide researchers to appropriate classes of techniques.Table of ContentsPreface ix Notation xi Introduction xv 1 The Continuous Wavelet Transform 1 1.1. Definition and Elementary Properties 1 1.2 Affine Operators 10 1.3 Filter Properties of the Wavelet Transform 12 1.4 Approximation Properties 22 1.5 Decay Behaviour 32 1.6 Group-Theoretical Foundations and Generalizations 36 1.7 Extension of the One-Dimensional Wavelet Transform to Sobolev Spaces 59 Exercises 69 2 The Discrete Wavelet Transform 73 2.1 Wavelet Frames 73 2.2 Multiscale Analysis 97 2.3 Fast Wavelet Transform 121 2.4 One-Dimensional Orthogonal Wavelets 131 2.5 Two-Dimensional Orthogonal Wavelets 203 Exercises 226 3 Applications of the Wavelet Transform 231 3.1 Wavelet Analysis of One-Dimensional Signals 231 3.2 Quality Control of Texture 235 3.3 Data Compression in Digital Image Processing 239 3.4 Regularization of Inverse Problems 251 3.5 Wavelet – Galerkin Methods for Two-Point boundary Value Problems 259 3.6 Schwarz Iterations Based on Wavelet Decompositions 278 3.7 An Outlook on Two-Dimensional Boundary Value Problems 300 Exercises 306 Appendix The Fourier Transform 309 References 313 Index 321
£148.45
John Wiley & Sons Inc Boundary Integral Equation Methods Applied to
Book SynopsisThe finite element method and the boundary element method are two computational methods available for designing structures ranging from aircraft and ships to dams and tunnels. This text presents the mathematical basis of the joint use of both methods and their computer implementation.Table of ContentsBasic principle and domains of application. I. BOUNDARY INTEGRAL EQUATIONS FOR STATIC PROBLEMS : Integral Equations and Representations for the Poisson Equation; Numerical Solution using Boundary Elements; Integral Equations and Representations for Elastostatics; Integral Representations of Gradients and Stresses on the Boundary; Some Classical Mathematical Results II. BOUNDARY INTEGRAL EQUATIONS FOR WAVE AND EVOLUTION PROBLEMS: Waves and Elastodynamics in Time Domain; Waves and Elastodynamics in Frequency Domain; Diffusion, Fluid Flow. III. ADVANCED TOPICS : Variational Boundary Integral Formulations; Exploitation of Geometrical Symmetry; Domain Derivative and Boundary Integral Eequations. IV. ADDITIONAL TOPICS IN SOLID MECHANICS : Boundary Integral Equations for Cracked Solids; Initial Strain or Stress: Inclusions, Elastoplasticity. APPENDICES : Tangential Differential Operators and Integration by Parts; Interpolation Functions and Numerical Integration. Bibliography. Index.
£158.35
John Wiley & Sons Inc Basic Mathematics for Chemists
Book SynopsisBasic Mathematics for Chemists aims to teach the maths that chemists need to know through the use of applications, data, examples and problems all drawn from chemistry. The author demystifies the maths, and shows how, where and why it is used in chemistry. The text assumes little prior knowledge of maths and starts from basic mathematical principles, including understanding equations, notation, basic functions and their priorities. It then covers more specialised functions such as logarithms and trigonometric functions before presenting chapters on calculus. In this edition, there is a new chapter on vectors and matrices. FEATURES * Written by a chemist for chemists * .Many examples, problems and applications. * Gentle introduction to the maths chemists needs to know * New chapter on vectors and matrices. * Fully worked examples and problems provided within each chapter CONTENTS: Preface; Equations, Functions and Graphs; Special Functions; Practical StatistiTable of ContentsEquations, Functions and Graphs. Special Functions. Practical Statistics. Differential Calculus. Integral Calculus. Differential Equations. Statistics for Theoretical Chemistry. Complex Numbers, Vectors, Determinants and Matrices. Appendices. Index.
£63.60
Wiley Monte Carlo Applications in Systems Engineering
Book SynopsisThis volume presents a unified framework for systems engineering and a systematic and rigorous source for a comprehensive description of the utilization of Monte Carlo methods in practical engineering problems. The author suggests that efficiency can be improved through such an integrated approach.Table of Contents1. Introduction - Probability and statistics 2. Basic concepts in system engineering 3. Basic concepts in Monte Carlo methods 4. Additional applications 5. Elements of uncertainty and uncertainty analysis 6. System transport 7. Realization of system transport Appendix
£190.76
John Wiley & Sons Inc Practical Statistics for Field Biology
Book SynopsisProvides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings.Table of ContentsMeasurement and Sampling Concepts. Processing Data. Presenting Data. Measuring the Average. Measuring Variability. Probability. Probability Distributions as Models of Dispersion. The Normal Distribution. Data Transformation. How Good are Our Estimates? The Basis of Statistical Testing. Analysing Frequencies. Measuring Correlations. Regression Analysis. Comparing Averages. Analysis of Variance - ANOVA. Multivariate Analysis. Appendices. Bibliography and Further Reading. Index.
£28.45
John Wiley & Sons Inc The Mathematical Theory of Selection
Book SynopsisIt is close to being a masterpiece...could well be the classic presentation of the area. Warren J. Ewens, University of Pennsylvania, USA Population genetics is concerned with the study of the genetic, ecological, and evolutionary factors that influence and change the genetic composition of populations. The emphasis here is on models that have a direct bearing on evolutionary quantitative genetics. Applications concerning the maintenance of genetic variation in quantitative traits and their dynamics under selection are treated in detail. * Provides a unified, self-contained and in-depth study of the theory of multilocus systems * Introduces the basic population-genetic models * Explores the dynamical and equilibrium properties of the distribution of quantitative traits under selection * Summarizes important results from more demanding sections in a comprehensible way * Employs a clear and logical presentation style Following an introduction to Trade Review"an excellent reference volume" (Zentralblatt Math, Vol. 959, No. 9 2001) "...Burger's text is without equal. This is a book that should grace shelves in both mathematics and biology...that provides yet another point of contact for two communities whose interests can only grow closer..." (SIAM Review, Vol. 43, No. 4) "This is a book that should grace shelves in both mathematics and biology departments." (Society for Industrial Applied Mathematics Review, Vol.43. No.4 2001) "...it is such a comprehensive compendium that it will become the first port of call for any mathematician..." (The Statistician, Vol. 51, No.2, 2002) "...the models described here provide a fundamental underpinning to our understanding of the properties of quantitative genetic variation...." (Journal of Evolutionary Biology, Vol. 14, 2001) "...a major and significant piece of work..." (Genetical Research)Table of ContentsElementary Population Genetics. Selection at Two or More Loci. Classical Mutation-Selection Models. Mutation-Selection Models for Quantitative Traits. Dynamical Equations for Quantitative Traits under Selection. Stabilizing Selection and Genetic Variation in Large Populations. Quantitative Variation and Selection. Appendix. References. Indexes.
£183.56
John Wiley & Sons Inc Sensitivity Analysis
Book SynopsisThis work is a guide to the principles behind sensitivity analysis. It suggests suitable methods for particular types of problem, which allows a greater understanding of the entire causal assessment chain. This makes the impact of source uncertainties and framing assumptions more transparent.Trade Review"The book has a fair price...I think this is a book that everyone who does modeling should buy. It can readily be read piecemeal...so it is ideal for leisurely self-study..." (Technometrics Vol. 42, No. 4 May 2001) "...this book will prove helpful in the solution of many modeling problems." (La Doc Sti, September 2000) "...presents many different sensitivity analysis methodologies and demonstrates their usefulness in scientific research." (Zentralblatt MATH, Vol. 961, 2001/11)Table of ContentsWhat is Sensitivity Analysis. Hitchhiker's Guide to Sensitivity Analysis. METHODS. Designs of Experiments. Screening Methods. Local Methods. Sampling-Based Methods. Reliability Algorithms: FORM and SORM Methods. Variance-Based Methods. Managing the Tyranny of Parameters in Mathematical Modelling of Physical Systems. Bayesian Sensitivity Analysis. Graphical Methods. APPLICATIONS. Practical Experience in Applying Sensitivity and Uncertainty Analysis. Scenario and Parametric Sensitivity and Uncertainty Analysis in Nuclear Waste Disposal Risk Assessment: The Case of GESAMAC. Sensitivity Analysis for Signal Extraction in Economic Time Series. A Dataless Precalibration Analysis in Solid State Physics. Appplication of First-Order (FORM) and Second-Order (SORM) Reliability Methods: Analysis and Interpretation of Sensitivity Measures Related to Groundwater Pressure Decreases and Resulting Ground Subsidence. One-at-a-Time and Mini-Global Analyses for Characterizing Model Sensitivity in the Nonlinear Ozone Predictions from the US EPA Regional Acid Deposition Model (RADM). Comparing Different Sensitivity Analysis Methods on a Chemical Reactions Model. An Application of Sensitivity Analysis to Fish Population Dynamics. Global Sensitivity Analysis: A Quality Assurance Tool in Environmental Policy Modelling. CONCLUSIONS. Assuring the Quality of Models Designed for Predictive Tasks. Fortune and Future of Sensitivity Analysis. References. Appendix. Index.
£133.16
John Wiley and Sons Ltd Introduction to Ecological Modelling
Book SynopsisAt present, most books on ecological modelling rely on very complex mathematics, resulting in students and researchers shying away from investigating the potential uses of ecological models and their methods of construction. This new book aims to open up this exciting area to a much wider audience.Trade Review"Teachers of courses on ecological modelling will find [this book] a useful source-book at a competitive price."Table of ContentsIntroduction: Themes Of Ecological Modelling. Probability Of Population Extinction. Looking For Cycles: The Dynamics Of Predators And Their Prey. Population Dynamics Of Species With Complex Life-Histories. Dynamics Of Ecological Communities. Spatial Models And Thresholds. Disease And Biological Control. Answers To Questions. Glossary Of Symbols And Terms. References. Index
£75.56
John Wiley and Sons Ltd Mathematics
Book SynopsisThis work aims to teach simple mathematics using geological examples to illustrate mathematical ideas. This approach emphasizes the relevance of mathematics to geology, helps to motivate the reader and gives examples of mathematical concepts in a context familiar to the reader.Table of ContentsPreface. 1. Mathematics as a tool for solving geological problems. 2. Common relationships between geological variables. 3. Equations and how to manipulate them. 4. More advanced equation manipulation. 5. Trigonometry. 6. More about graphs. 7. Statistics. 8. Differential calculus. 9. Integral calculus. Appendix A - useful equations. Appendix B - answers to problems. Index
£65.66
John Wiley and Sons Ltd Multiplepoint Geostatistics
Book SynopsisThis book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable rTrade Review"I benefited from this book and plan to keep it as a resource on my bookshelf. I recommend Multiple-point Geostatistics: Stochastic Modeling with Training Images to my peers in mathematical geosciences." (Mathematical Geosciences, 2016)Table of ContentsPreface, vii Acknowledgments, xi Part I Concepts I.1 Hiking in the Sierra Nevada, 3 I.2 Spatial estimation based on random function theory, 7 I.3 Universal kriging with training images, 29 I.4 Stochastic simulations based on random function theory, 49 I.5 Stochastic simulation without random function theory, 59 I.6 Returning to the Sierra Nevada, 75 Part II Methods II.1 Introduction, 87 II.2 The algorithmic building blocks, 91 II.3 Multiple-point geostatistics algorithms, 155 II.4 Markov random fields, 173 II.5 Nonstationary modeling with training images, 183 II.6 Multivariate modeling with training images, 199 II.7 Training image construction, 221 II.8 Validation and quality control, 239 II.9 Inverse modeling with training images, 259 II.10 Parallelization, 295 Part III Applications III.1 Reservoir forecasting – the West Coast of Africa (WCA) reservoir, 303 III.2 Geological resources modeling in mining, 329 Coauthored by Cristian P´erez, Julian M. Ortiz, & Alexandre Boucher III.3 Climate modeling application – the case of the Murray–Darling Basin, 345 Index, 361
£82.76
John Wiley & Sons Inc Symbolic Mathematics for Chemists A Guide for
Book SynopsisAn essential guide to using Maxima, a popular open source symbolic mathematics engine to solve problems, build models, analyze data and explore fundamental concepts Symbolic Mathematics for Chemists offers students of chemistry a guide to Maxima, a popular open source symbolic mathematics engine that can be used to solve problems, build models, analyze data, and explore fundamental chemistry concepts. The author a noted expert in the field focuses on the analysis of experimental data obtained in a laboratory setting and the fitting of data and modeling experiments. The text contains a wide variety of illustrative examples and applications in physical chemistry, quantitative analysis and instrumental techniques. Designed as a practical resource, the book is organized around a series of worksheets that are provided in a companion website. Each worksheet has clearly defined goals and learning objectives and a detailed abstract that provides motivation and Table of ContentsPreface xiii 1 Fundamentals 1 1.1 Getting Started With wxMaxima 1 1.1.1 Input Cells 2 1.1.2 The Toolbar 3 1.1.3 The Menus 3 1.1.4 Command History 4 1.1.5 Basic Arithmetic 5 1.1.6 Mathematical Functions 7 1.1.7 Assigning Variables 8 1.1.8 Defining Functions 10 1.1.9 Comments, Images, and Sectioning 12 1.2 A Tour of the General Math Pane 12 1.2.1 Basic Plotting 13 1.2.1.1 Plotting Multiple Curves 14 1.2.1.2 Parametric Plots 15 1.2.1.3 Discrete Plots 15 1.2.1.4 Three-Dimensional Plots 17 1.2.2 Basic Algebra 18 1.2.2.1 Equations 18 1.2.2.2 Substitutions 18 1.2.2.3 Simplification 20 1.2.2.4 Solving Equations 21 1.2.2.5 Simplifying Trigonometric and Exponential Functions 21 1.2.3 Basic Calculus 22 1.2.3.1 Limits 22 1.2.3.2 Differentiation 23 1.2.3.3 Series 24 1.2.3.4 Integration 25 1.2.4 Differential Equations 28 1.3 Controlling Execution 28 1.4 Using Packages 30 2 Storing and Transforming Data 33 2.1 Numbers 33 2.1.1 Floating Point Numbers 33 2.1.2 Integers and Rational Numbers 37 2.1.3 Complex Numbers 38 2.1.4 Constants 42 2.1.5 Units and Physical Constants 43 2.2 Boolean Expressions and Predicates 47 2.2.1 Relational Operators 47 2.2.2 Logical Operators 48 2.2.3 Predicates 49 2.3 Lists 51 2.3.1 List Assignments 51 2.3.2 Indexing List Items 52 2.3.3 Arithmetic with Lists 52 2.3.4 Building and Editing Lists 54 2.3.4.1 Adding Items 54 2.3.4.2 Deleting Items 55 2.3.5 Nested Lists 55 2.3.6 Sublists 56 2.4 Matrices 57 2.4.1 Row and Column Vectors 57 2.4.2 Indexing Matrices 58 2.4.3 Entering Matrices 59 2.4.4 Assigning Matrices 60 2.4.5 Editing Matrices 61 2.4.6 Reading and Writing Matrices From Files 63 2.4.7 Transforming Data in a Matrix 65 2.5 Strings 66 2.5.1 Using String Functions toWork with Files 67 3 Plotting Data and Functions 71 3.1 Plotting in Two Dimensions 71 3.1.1 Changing Plot Size and Resolution 71 3.1.2 Plotting Multiple Curves 73 3.1.3 Changing Axis Ranges 74 3.1.4 Plotting Complex Functions 74 3.1.5 Plotting Data 74 3.1.5.1 Plotting Data in Separate X, Y Lists 75 3.1.5.2 Plotting Data as Lists of X, Y Points 75 3.1.5.3 Plotting Data in Matrices 76 3.1.5.4 Plotting Data with Units 76 3.1.5.5 Plotting Functions and Data Together 77 3.1.6 Adding Text Labels to Graphs 77 3.1.7 Plotting Rapidly Rising Functions 78 3.1.7.1 Solving Axis Scaling Problems 81 3.1.7.2 Positioning the Legend 83 3.1.8 Parametric Plots 84 3.1.9 Implicit Plots 87 3.1.10 Histograms 89 3.2 Plotting inThree Dimensions 91 3.2.1 Plotting Functions of x, y, andz 91 3.2.2 Plotting Multiple Surfaces 93 3.2.3 Plotting in Spherical Coordinates 94 3.2.4 Plotting in Cylindrical Coordinates 95 3.2.5 Parametric Surface Plots 96 3.2.6 Plotting DiscreteThree-Dimensional Data 98 3.2.7 Contour Plotting 99 4 Programming Maxima 103 4.1 Nouns and Verbs 103 4.2 Writing Multiline Functions 106 4.3 Decision Making 108 4.4 Recursive Functions 109 4.5 Contexts 110 4.6 Iteration 114 4.6.1 Indexed Loops 114 4.6.2 Conditional Loops 116 4.6.3 Looping Over Lists 117 4.6.4 Nested Loops 118 5 Algebra 119 5.1 Series 119 5.1.1 Simplifying Sums 120 5.1.2 Reindexing and Combining Sums 122 5.1.3 Applying Functions to Sums and Products 123 5.2 Products 124 5.3 Equations 126 5.3.1 Simplifying Equations 126 5.3.2 Simplifying Trigonometric and Exponential Functions 127 5.3.3 Extracting Expressions From an Equation 128 5.3.4 Expanding Expressions 131 5.3.5 Factoring Expressions 134 5.3.6 Substitution 135 5.3.7 Solving an Equation Symbolically 138 5.3.7.1 Handling Multiple Solutions 139 5.3.8 Solving an Equation Numerically 140 5.4 Systems of Equations 141 5.4.1 Eliminating Variables 141 5.4.2 Solving Systems of EquationsWithout Elimination 143 5.5 Interpolation 144 5.5.1 Piecewise Linear Interpolation 146 5.5.2 Spline Interpolation 147 6 Differentiation, Integration, and Minimization 149 6.1.1 Limits for Discontinuous Functions 151 6.1.2 Limits for Indefinite Functions 152 6.2 Differentials 153 6.3 Derivatives 154 6.3.1 Explicit Partial and Total Derivatives 156 6.3.2 Derivatives Evaluated at a Specific Point 157 6.3.3 Higher-Order Derivatives 158 6.3.4 Mixed Derivatives 159 6.3.5 Assigning Partial Derivatives 160 6.3.5.1 Partial Derivatives from Total Differential Expansions 161 6.3.5.2 Writing Total Differential Expansions in Terms of New Variables 161 6.3.6 Implicit Differentiation 162 6.4 Maxima, Minima, and Inflection Points 164 6.4.1 Critical Points of Surfaces 167 6.4.2 Numerical Minimization 169 6.5 Integration 173 6.5.1 Integration Constants 174 6.5.2 Definite Integration 174 6.5.3 When Symbolic Integration Fails 175 6.5.4 Numerical Integration 178 6.5.4.1 Numerical Integration over Infinite Intervals 179 6.5.4.2 Numerical Integration with Strongly Oscillating Integrands 180 6.5.4.3 Numerical Integration with Discontinuous Integrands 181 6.5.5 Multiple Integration 182 6.5.6 Discrete Integration 183 6.6 Power Series 186 6.6.1 Testing Power Series for Convergence 186 6.7 Taylor Series 187 6.7.1 Exploring Function Properties with Taylor Series 188 6.7.2 The Remainder Term 190 6.7.3 Taylor Series for Multivariate Functions 191 6.7.4 Approximating Taylor Series 191 7 Matrices and Vectors 193 7.1 Vectors 193 7.1.1 Vector Arithmetic 194 7.1.2 The Dot Product 195 7.1.3 Vector Lengths and Angles 196 7.1.4 The Cross Product 197 7.1.5 Angular Momentum 198 7.1.6 Vector Algebra 199 7.2 Matrices 200 7.2.1 Matrix Arithmetic 201 7.2.2 The Transpose 201 7.2.3 The Matrix Product 202 7.2.4 Determinants 203 7.2.5 The Inverse of a Matrix 206 7.2.6 Matrix Algebra 207 7.2.7 Eigenvalues and Eigenvectors 211 7.2.7.1 Application: Energies and Molecular Orbitals of Ethylene 212 7.2.7.2 Eigenvalues and Eigenvectors for Symmetric Matrices 214 7.2.7.3 Matrix Diagonalization 216 7.3 Vector Calculus 217 7.3.1 Derivative of a Vector with Respect to a Scalar 217 7.3.2 The Jacobian 218 7.3.3 The Gradient 220 7.3.4 The Laplacian 222 7.3.5 The Divergence 224 7.3.6 The Curl 225 8 Error Analysis 227 8.1 Classifying Experimental Errors 227 8.1.1 Systematic Error 229 8.1.2 Random Error 230 8.2 Probability Density 230 8.2.1 Discrete Probability Distributions 230 8.2.2 The Poisson Distribution 232 8.2.3 Continuous Probability Distributions 235 8.2.4 The Normal Distribution 236 8.3 Estimating Precision 238 8.3.1 Standard Error of the Mean 240 8.3.2 Confidence Interval of the Mean 240 8.4 Hypothesis Testing 241 8.4.1 Comparing a Mean with a True Value 243 8.4.2 Comparing Variances 244 8.4.3 Comparing Two Sample Means 246 8.5 Propagation of Error 249 8.5.1 Propagation of Independent Systematic Errors 249 8.5.2 Propagation of Independent Random Errors 251 8.5.3 Covariance and Correlation 253 9 Fitting Data to a Straight Line 257 9.1 The Ordinary Least-Squares Method 259 9.1.1 Using Built-In Functions 260 9.1.2 Error Estimates for the Slope and the Intercept 263 9.1.3 The Determination Coefficient 266 9.1.4 Residual Analysis 268 9.1.5 Testing the Fit Parameters 271 9.1.6 Testing for Lack-of-Fit 272 9.2 Multiple Linear Regression 274 9.2.1 Matrix Form of Multiple Linear Regression 275 9.2.2 Estimating the Errors in the Fit Parameters in MLR 277 9.2.3 Example: Microwave Rotational Spectrum of HCl 278 9.2.4 Detecting and Dealing with Outliers 281 9.3 WLS 285 9.3.1 The Fit Parameters inWLS 286 9.3.2 Error Estimates for theWLS Fit Parameters 286 9.3.3 Finding theWeights 287 9.3.4 Residual Analysis inWLS 288 9.3.5 Evaluating Goodness-of-Fit 288 9.4 Fitting Data to a Line with Errors in Both X and Y 289 9.4.1 Finding Fit Parameters in TLS 290 9.4.2 Error Estimates for the TLS Fit Parameters 292 9.4.3 Assessing Goodness-of-Fit in TLS 293 9.4.4 Multiple Linear Regression with TLS 293 9.5 Calibration and Standard Additions 294 9.5.1 Error Estimates for Calibrated Values 294 9.5.2 Standard Additions 295 10 Fitting Data to a Curve 299 10.1 Transforming Data to a Linear Form 299 10.2 Polynomial Least-Squares Fitting 302 10.2.1 How Many Fit Parameters Are Needed? 304 10.3 Nonlinear Least-Squares Models 306 10.4 Estimating Error in Nonlinear Fit Parameters 310 10.4.1 Estimating Parameter Errors with the Jackknife Method 311 10.4.2 Estimating Parameter Errors with the Bootstrap Method 313 11 Differential Equations 317 11.1 Symbolic Solutions of ODEs 318 11.1.1 Initial Value Problems 320 11.1.2 Boundary Value Problems 322 11.2 Power Series Solution of ODEs 325 11.3 Direction Fields 329 11.3.1 Direction Fields with Adjustable Parameters 331 11.3.2 Direction Fields and Autonomous Equations 332 11.4 Solving Systems of Linear Differential Equations 335 11.5 Numerical Solution of ODEs 338 11.6 Solving Partial Differential Equations 340 12 Operators and Integral Transforms 343 12.1 Defining Operators 344 12.2 Fourier Series 347 12.3 Fourier Transforms 351 12.3.1 The Fast Fourier Transform 355 12.4 The Laplace Transform 357 Glossary 359 References 367 Index 371
£72.15
John Wiley & Sons Inc Two and Three Dimensional Calculus
Book SynopsisCovers multivariable calculus, starting from the basics and leading up to the three theorems of Green, Gauss, and Stokes, but always with an eye on practical applications. Written for a wide spectrum of undergraduate students by an experienced author, this book provides a very practical approach to advanced calculusstarting from the basics and leading up to the theorems of Green, Gauss, and Stokes. It explains, clearly and concisely, partial differentiation, multiple integration, vectors and vector calculus, and provides end-of-chapter exercises along with their solutions to aid the readers' understanding. Written in an approachable style and filled with numerous illustrative examples throughout, Two and Three Dimensional Calculus: with Applications in Science and Engineering assumes no prior knowledge of partial differentiation or vectors and explains difficult concepts with easy to follow examples. Rather than concentrating on mathematical structures, tTable of ContentsPreface xi 1 Revision of One-Dimensional Calculus 1 1.1 Limits and Convergence 1 1.2 Differentiation 3 1.2.1 Rules for Differentiation 5 1.2.2 Mean Value Theorem 7 1.2.3 Taylor’s Series 8 1.2.4 Maxima and Minima 12 1.2.5 Numerical Differentiation 13 1.3 Integration 16 Exercises 22 2 Partial Differentiation 25 2.1 Introduction 25 2.2 Differentials 29 2.2.1 Small Errors 30 2.3 Total Derivative 33 2.4 Chain Rule 36 2.4.1 Leibniz Rule 39 2.4.2 Chain Rule in n Dimensions 41 2.4.3 Implicit Functions 42 2.5 Jacobian 43 2.6 Higher Derivatives 46 2.6.1 Higher Differentials 49 2.7 Taylor’sTheorem 50 2.8 Conjugate Functions 52 2.9 Case Study:Thermodynamics 54 Exercises 58 3 Maxima and Minima 61 3.1 Introduction 61 3.2 Maxima, Minima and Saddle Points 63 3.3 Lagrange Multipliers 74 3.3.1 Generalisations 77 3.4 Optimisation 81 3.4.1 Hill Climbing Techniques 81 Exercises 85 4 Vector Algebra 89 4.1 Introduction 89 4.2 Vector Addition 90 4.3 Components 92 4.4 Scalar Product 94 4.5 Vector Product 97 4.5.1 Scalar Triple Product 102 4.5.2 Vector Triple Product 105 Exercises 106 5 Vector Differentiation 109 5.1 Introduction 109 5.2 Differential Geometry 111 5.2.1 Space Curves 112 5.2.2 Surfaces 120 5.3 Mechanics 129 Exercises 135 6 Gradient, Divergence, and Curl 139 6.1 Introduction 139 6.2 Gradient 139 6.3 Divergence 143 6.4 Curl 145 6.5 Vector Identities 146 6.6 Conjugate Functions 151 Exercises 154 7 Curvilinear Co-ordinates 157 7.1 Introduction 157 7.2 Curved Axes and Scale Factors 157 7.3 Curvilinear Gradient, Divergence, and Curl 161 7.3.1 Gradient 161 7.3.2 Divergence 163 7.3.3 Curl 165 7.4 Further Results and Tensors 166 7.4.1 Tensor Notation 166 7.4.2 Covariance and Contravariance 168 Exercises 171 8 PathIntegrals 173 8.1 Introduction 173 8.2 Integration Along a Curve 173 8.3 Practical Applications 181 Exercises 186 9 Multiple Integrals 191 9.1 Introduction 191 9.2 The Double Integral 191 9.2.1 Rotation and Translation 199 9.2.2 Change of Order of Integration 201 9.2.3 Plane Polar Co-ordinates 203 9.2.4 Applications of Double Integration 208 9.3 Triple Integration 213 9.3.1 Cylindrical and Spherical Polar Co-ordinates 219 9.3.2 Applications of Triple Integration 227 Exercises 233 10 Surface Integrals 241 10.1 Introduction 241 10.2 Green’s Theorem in the Plane 242 10.3 Integration over a Curved Surface 246 10.4 Applications of Surface Integration 253 Exercises 256 11 Integral Theorems 259 11.1 Introduction 259 11.2 Stokes’ Theorem 260 11.3 Gauss’ DivergenceTheorem 268 11.3.1 Green’s Second Identity 275 11.4 Co-ordinate-Free Definitions 277 11.5 Applications of Integral Theorems 279 11.5.1 Electromagnetic Theory 279 11.5.1.1 Maxwell’s Equations 279 11.5.2 Fluid Mechanics 283 11.5.3 ElasticityTheory 287 11.5.4 Heat Transfer 297 Exercises 298 12 Solutions and Answers to Exercises 301 References 375 Index 377
£45.55
John Wiley & Sons Inc Statistics and Probability with Applications for Engineers and Scientists Using MINITAB R and JMP
Book SynopsisIntroduces basic concepts in probability and statistics to data science students, as well as engineers and scientists Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data miningincluding big data, classification, machine learning, and visualizationis featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book's companion website. Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken iTable of ContentsPreface xvii Acknowledgments xxi About The Companion Site xxiii 1 Introduction 1 1.1 Designed Experiment 2 1.1.1 Motivation for the Study 2 1.1.2 Investigation 3 1.1.3 Changing Criteria 3 1.1.4 A Summary of the Various Phases of the Investigation 5 1.2 A Survey 6 1.3 An Observational Study 6 1.4 A Set of Historical Data 7 1.5 A Brief Description of What is Covered in this Book 7 Part I Fundamentals of Probability and Statistics 2 Describing Data Graphically and Numerically 13 2.1 Getting Started with Statistics 14 2.1.1 What is Statistics? 14 2.1.2 Population and Sample in a Statistical Study 14 2.2 Classification of Various Types of Data 18 2.2.1 Nominal Data 18 2.2.2 Ordinal Data 19 2.2.3 Interval Data 19 2.2.4 Ratio Data 19 2.3 Frequency Distribution Tables for Qualitative and Quantitative Data 20 2.3.1 Qualitative Data 21 2.3.2 Quantitative Data 24 2.4 Graphical Description of Qualitative and Quantitative Data 30 2.4.1 Dot Plot 30 2.4.2 Pie Chart 31 2.4.3 Bar Chart 33 2.4.4 Histograms 37 2.4.5 Line Graph 44 2.4.6 Stem-and-Leaf Plot 45 2.5 Numerical Measures of Quantitative Data 50 2.5.1 Measures of Centrality 51 2.5.2 Measures of Dispersion 56 2.6 Numerical Measures of Grouped Data 67 2.6.1 Mean of a Grouped Data 67 2.6.2 Median of a Grouped Data 68 2.6.3 Mode of a Grouped Data 69 2.6.4 Variance of a Grouped Data 69 2.7 Measures of Relative Position 70 2.7.1 Percentiles 71 2.7.2 Quartiles 72 2.7.3 Interquartile Range (IQR) 72 2.7.4 Coefficient of Variation 73 2.8 Box-Whisker Plot 75 2.8.1 Construction of a Box Plot 75 2.8.2 How to Use the Box Plot 76 2.9 Measures of Association 80 2.10 Case Studies 84 2.10.1 About St. Luke’s Hospital 85 2.11 Using JMP 86 Review Practice Problems 87 3 Elements of Probability 97 3.1 Introduction 97 3.2 Random Experiments, Sample Spaces, and Events 98 3.2.1 Random Experiments and Sample Spaces 98 3.2.2 Events 99 3.3 Concepts of Probability 103 3.4 Techniques of Counting Sample Points 108 3.4.1 Tree Diagram 108 3.4.2 Permutations 110 3.4.3 Combinations 110 3.4.4 Arrangements of n Objects Involving Several Kinds of Objects 111 3.5 Conditional Probability 113 3.6 Bayes’s Theorem 116 3.7 Introducing Random Variables 120 Review Practice Problems 122 4 Discrete Random Variables and Some Important Discrete Probability Distributions 128 4.1 Graphical Descriptions of Discrete Distributions 129 4.2 Mean and Variance of a Discrete Random Variable 130 4.2.1 Expected Value of Discrete Random Variables and Their Functions 130 4.2.2 The Moment-Generating Function-Expected Value of a Special Function of X 133 4.3 The Discrete Uniform Distribution 136 4.4 The Hypergeometric Distribution 137 4.5 The Bernoulli Distribution 141 4.6 The Binomial Distribution 142 4.7 The Multinomial Distribution 146 4.8 The Poisson Distribution 147 4.8.1 Definition and Properties of the Poisson Distribution 147 4.8.2 Poisson Process 148 4.8.3 Poisson Distribution as a Limiting Form of the Binomial 148 4.9 The Negative Binomial Distribution 153 4.10 Some Derivations and Proofs (Optional) 156 4.11 A Case Study 156 4.12 Using JMP 157 Review Practice Problems 157 5 Continuous Random Variables and Some Important Continuous Probability Distributions 164 5.1 Continuous Random Variables 165 5.2 Mean and Variance of Continuous Random Variables 168 5.2.1 Expected Value of Continuous Random Variables and Their Functions 168 5.2.2 The Moment-Generating Function and Expected Value of a Special Function of X 171 5.3 Chebyshev’s Inequality 173 5.4 The Uniform Distribution 175 5.4.1 Definition and Properties 175 5.4.2 Mean and Standard Deviation of the Uniform Distribution 178 5.5 The Normal Distribution 180 5.5.1 Definition and Properties 180 5.5.2 The Standard Normal Distribution 182 5.5.3 The Moment-Generating Function of the Normal Distribution 187 5.6 Distribution of Linear Combination of Independent Normal Variables 189 5.7 Approximation of the Binomial and Poisson Distributions by the Normal Distribution 193 5.7.1 Approximation of the Binomial Distribution by the Normal Distribution 193 5.7.2 Approximation of the Poisson Distribution by the Normal Distribution 196 5.8 A Test of Normality 196 5.9 Probability Models Commonly used in Reliability Theory 201 5.9.1 The Lognormal Distribution 202 5.9.2 The Exponential Distribution 206 5.9.3 The Gamma Distribution 211 5.9.4 The Weibull Distribution 214 5.10 A Case Study 218 5.11 Using JMP 219 Review Practice Problems 220 6 Distribution of Functions Of Random Variables 228 6.1 Introduction 229 6.2 Distribution Functions of Two Random Variables 229 6.2.1 Case of Two Discrete Random Variables 229 6.2.2 Case of Two Continuous Random Variables 232 6.2.3 The Mean Value and Variance of Functions of Two Random Variables 233 6.2.4 Conditional Distributions 235 6.2.5 Correlation between Two Random Variables 238 6.2.6 Bivariate Normal Distribution 241 6.3 Extension to Several Random Variables 244 6.4 The Moment-Generating Function Revisited 245 Review Practice Problems 249 7 Sampling Distributions 253 7.1 Random Sampling 253 7.1.1 Random Sampling from an Infinite Population 254 7.1.2 Random Sampling from a Finite Population 256 7.2 The Sampling Distribution of the Sample Mean 258 7.2.1 Normal Sampled Population 258 7.2.2 Nonnormal Sampled Population 258 7.2.3 The Central Limit Theorem 259 7.3 Sampling from a Normal Population 264 7.3.1 The Chi-Square Distribution 264 7.3.2 The Student t-Distribution 271 7.3.3 Snedecor’s F-Distribution 276 7.4 Order Statistics 279 7.4.1 Distribution of the Largest Element in a Sample 280 7.4.2 Distribution of the Smallest Element in a Sample 281 7.4.3 Distribution of the Median of a Sample and of the kth Order Statistic 282 7.4.4 Other Uses of Order Statistics 284 7.5 Using JMP 286 Review Practice Problems 286 8 Estimation of Population Parameters 289 8.1 Introduction 290 8.2 Point Estimators for the Population Mean and Variance 290 8.2.1 Properties of Point Estimators 292 8.2.2 Methods of Finding Point Estimators 295 8.3 Interval Estimators for the Mean μ of a Normal Population 301 8.3.1 σ2 Known 301 8.3.2 σ2 Unknown 304 8.3.3 Sample Size is Large 306 8.4 Interval Estimators for The Difference of Means of Two Normal Populations 313 8.4.1 Variances are Known 313 8.4.2 Variances are Unknown 314 8.5 Interval Estimators for the Variance of a Normal Population 322 8.6 Interval Estimator for the Ratio of Variances of Two Normal Populations 327 8.7 Point and Interval Estimators for the Parameters of Binomial Populations 331 8.7.1 One Binomial Population 331 8.7.2 Two Binomial Populations 334 8.8 Determination of Sample Size 338 8.8.1 One Population Mean 339 8.8.2 Difference of Two Population Means 339 8.8.3 One Population Proportion 340 8.8.4 Difference of Two Population Proportions 341 8.9 Some Supplemental Information 343 8.10 A Case Study 343 8.11 Using JMP 343 Review Practice Problems 344 9 Hypothesis Testing 352 9.1 Introduction 353 9.2 Basic Concepts of Testing a Statistical Hypothesis 353 9.2.1 Hypothesis Formulation 353 9.2.2 Risk Assessment 355 9.3 Tests Concerning the Mean of a Normal Population Having Known Variance 358 9.3.1 Case of a One-Tail (Left-Sided) Test 358 9.3.2 Case of a One-Tail (Right-Sided) Test 362 9.3.3 Case of a Two-Tail Test 363 9.4 Tests Concerning the Mean of a Normal Population Having Unknown Variance 372 9.4.1 Case of a Left-Tail Test 372 9.4.2 Case of a Right-Tail Test 373 9.4.3 The Two-Tail Case 374 9.5 Large Sample Theory 378 9.6 Tests Concerning the Difference of Means of Two Populations Having Distributions with Known Variances 380 9.6.1 The Left-Tail Test 380 9.6.2 The Right-Tail Test 381 9.6.3 The Two-Tail Test 383 9.7 Tests Concerning the Difference of Means of Two Populations Having Normal Distributions with Unknown Variances 388 9.7.1 Two Population Variances are Equal 388 9.7.2 Two Population Variances are Unequal 392 9.7.3 The Paired t-Test 395 9.8 Testing Population Proportions 401 9.8.1 Test Concerning One Population Proportion 401 9.8.2 Test Concerning the Difference Between Two Population Proportions 405 9.9 Tests Concerning the Variance of a Normal Population 410 9.10 Tests Concerning the Ratio of Variances of Two Normal Populations 414 9.11 Testing of Statistical Hypotheses using Confidence Intervals 418 9.12 Sequential Tests of Hypotheses 422 9.12.1 A One-Tail Sequential Testing Procedure 422 9.12.2 A Two-Tail Sequential Testing Procedure 427 9.13 Case Studies 430 9.14 Using JMP 431 Review Practice Problems 431 Part II Statistics in Actions 10 Elements of Reliability Theory 445 10.1 The Reliability Function 446 10.1.1 The Hazard Rate Function 446 10.1.2 Employing the Hazard Function 455 10.2 Estimation: Exponential Distribution 457 10.3 Hypothesis Testing: Exponential Distribution 465 10.4 Estimation: Weibull Distribution 467 10.5 Case Studies 472 10.6 Using JMP 474 Review Practice Problems 474 11 On Data Mining 476 11.1 Introduction 476 11.2 What is Data Mining? 477 11.2.1 Big Data 477 11.3 Data Reduction 478 11.4 Data Visualization 481 11.5 Data Preparation 490 11.5.1 Missing Data 490 11.5.2 Outlier Detection and Remedial Measures 491 11.6 Classification 492 11.6.1 Evaluating a Classification Model 493 11.7 Decision Trees 499 11.7.1 Classification and Regression Trees (CART) 500 11.7.2 Further Reading 511 11.8 Case Studies 511 11.9 Using JMP 512 Review Practice Problems 512 12 Cluster Analysis 518 12.1 Introduction 518 12.2 Similarity Measures 519 12.2.1 Common Similarity Coefficients 524 12.3 Hierarchical Clustering Methods 525 12.3.1 Single Linkage 526 12.3.2 Complete Linkage 531 12.3.3 Average Linkage 534 12.3.4 Ward’s Hierarchical Clustering 536 12.4 Nonhierarchical Clustering Methods 538 12.4.1 K-Means Method 538 12.5 Density-Based Clustering 544 12.6 Model-Based Clustering 547 12.7 A Case Study 552 12.8 Using JMP 553 Review Practice Problems 553 13 Analysis of Categorical Data 558 13.1 Introduction 558 13.2 The Chi-Square Goodness-of-Fit Test 559 13.3 Contingency Tables 568 13.3.1 The 2 × 2 Case with Known Parameters 568 13.3.2 The 2 × 2 Case with Unknown Parameters 570 13.3.3 The r × s Contingency Table 572 13.4 Chi-Square Test for Homogeneity 577 13.5 Comments on the Distribution of the Lack-of-Fit Statistics 581 13.6 Case Studies 583 13.7 Using JMP 584 Review Practice Problems 585 14 Nonparametric Tests 591 14.1 Introduction 591 14.2 The Sign Test 592 14.2.1 One-Sample Test 592 14.2.2 The Wilcoxon Signed-Rank Test 595 14.2.3 Two-Sample Test 598 14.3 Mann–Whitney (Wilcoxon) W Test for Two Samples 604 14.4 Runs Test 608 14.4.1 Runs above and below the Median 608 14.4.2 The Wald–Wolfowitz Run Test 611 14.5 Spearman Rank Correlation 614 14.6 Using JMP 618 Review Practice Problems 618 15 Simple Linear Regression Analysis 622 15.1 Introduction 623 15.2 Fitting the Simple Linear Regression Model 624 15.2.1 Simple Linear Regression Model 624 15.2.2 Fitting a Straight Line by Least Squares 627 15.2.3 Sampling Distribution of the Estimators of Regression Coefficients 631 15.3 Unbiased Estimator of σ2 637 15.4 Further Inferences Concerning Regression Coefficients (β0, β1), E(Y ), and Y 639 15.4.1 Confidence Interval for β1 with Confidence Coefficient (1 − α) 639 15.4.2 Confidence Interval for β0 with Confidence Coefficient (1 − α) 640 15.4.3 Confidence Interval for E(Y |X) with Confidence Coefficient (1 − α) 642 15.4.4 Prediction Interval for a Future Observation Y with Confidence Coefficient (1 − α) 645 15.5 Tests of Hypotheses for β0 and β1 652 15.5.1 Test of Hypotheses for β1 652 15.5.2 Test of Hypotheses for β0 652 15.6 Analysis of Variance Approach to Simple Linear Regression Analysis 659 15.7 Residual Analysis 665 15.8 Transformations 674 15.9 Inference About ρ 681 15.10A Case Study 683 15.11 Using JMP 684 Review Practice Problems 684 16 Multiple Linear Regression Analysis 693 16.1 Introduction 694 16.2 Multiple Linear Regression Models 694 16.3 Estimation of Regression Coefficients 699 16.3.1 Estimation of Regression Coefficients Using Matrix Notation 701 16.3.2 Properties of the Least-Squares Estimators 703 16.3.3 The Analysis of Variance Table 704 16.3.4 More Inferences about Regression Coefficients 706 16.4 Multiple Linear Regression Model Using Quantitative and Qualitative Predictor Variables 714 16.4.1 Single Qualitative Variable with Two Categories 714 16.4.2 Single Qualitative Variable with Three or More Categories 716 16.5 Standardized Regression Coefficients 726 16.5.1 Multicollinearity 728 16.5.2 Consequences of Multicollinearity 729 16.6 Building Regression Type Prediction Models 730 16.6.1 First Variable to Enter into the Model 730 16.7 Residual Analysis and Certain Criteria for Model Selection 734 16.7.1 Residual Analysis 734 16.7.2 Certain Criteria for Model Selection 735 16.8 Logistic Regression 740 16.9 Case Studies 745 16.10 Using JMP 748 Review Practice Problems 748 17 Analysis of Variance 757 17.1 Introduction 758 17.2 The Design Models 758 17.2.1 Estimable Parameters 758 17.2.2 Estimable Functions 760 17.3 One-Way Experimental Layouts 761 17.3.1 The Model and Its Analysis 761 17.3.2 Confidence Intervals for Treatment Means 767 17.3.3 Multiple Comparisons 773 17.3.4 Determination of Sample Size 780 17.3.5 The Kruskal–Wallis Test for One-Way Layouts (Nonparametric Method) 781 17.4 Randomized Complete Block (RCB) Designs 785 17.4.1 The Friedman Fr-Test for Randomized Complete Block Design (Nonparametric Method) 792 17.4.2 Experiments with One Missing Observation in an RCB-Design Experiment 794 17.4.3 Experiments with Several Missing Observations in an RCB-Design Experiment 795 17.5 Two-Way Experimental Layouts 798 17.5.1 Two-Way Experimental Layouts with One Observation per Cell 800 17.5.2 Two-Way Experimental Layouts with r > 1 Observations per Cell 801 17.5.3 Blocking in Two-Way Experimental Layouts 810 17.5.4 Extending Two-Way Experimental Designs to n-Way Experimental Layouts 811 17.6 Latin Square Designs 813 17.7 Random-Effects and Mixed-Effects Models 820 17.7.1 Random-Effects Model 820 17.7.2 Mixed-Effects Model 822 17.7.3 Nested (Hierarchical) Designs 824 17.8 A Case Study 831 17.9 Using JMP 832 Review Practice Problems 832 18 The 2k Factorial Designs 847 18.1 Introduction 848 18.2 The Factorial Designs 848 18.3 The 2k Factorial Designs 850 18.4 Unreplicated 2k Factorial Designs 859 18.5 Blocking in the 2k Factorial Design 867 18.5.1 Confounding in the 2k Factorial Design 867 18.5.2 Yates’s Algorithm for the 2k Factorial Designs 875 18.6 The 2k Fractional Factorial Designs 877 18.6.1 One-half Replicate of a 2k Factorial Design 877 18.6.2 One-quarter Replicate of a 2k Factorial Design 882 18.7 Case Studies 887 18.8 Using JMP 889 Review Practice Problems 889 19 Response Surfaces 897 19.1 Introduction 897 19.1.1 Basic Concepts of Response Surface Methodology 898 19.2 First-Order Designs 903 19.3 Second-Order Designs 917 19.3.1 Central Composite Designs (CCDs) 918 19.3.2 Some Other First-Order and Second-Order Designs 928 19.4 Determination of Optimum or Near-Optimum Point 936 19.4.1 The Method of Steepest Ascent 937 19.4.2 Analysis of a Fitted Second-Order Response Surface 941 19.5 Anova Table for a Second-Order Model 946 19.6 Case Studies 948 19.7 Using JMP 950 Review Practice Problems 950 20 Statistical Quality Control—Phase I Control Charts 958 21 Statistical Quality Control—Phase II Control Charts 960 Appendices 961 Appendix A Statistical Tables 962 Appendix B Answers to Selected Problems 969 Appendix C Bibliography 992 Index 1003
£104.36
John Wiley and Sons Ltd Mathematical Ecology of Populations and
Book SynopsisThis is a major new introductory textbook on mathematical ecology bridging the subdisciplines of population ecology and ecosystem ecology. The book is ideal for beginning graduate and advanced undergraduate students, with some background in basic calculus, linear algebra, and basic ecology.Trade Review"Nevertheless, it is an excellent summary which will sweep away the cobwebs from the mind of someone who has learnt this stuff at some time in the past. . . It would be ideal as a text for a course taught in a mathematics department, to convince mathematics students that their skills in differential equations can be applied to ecological problems." (Austral Ecology, 2011) "Its best feature a the scientific soundness t hat permeates the whole book, founded on a robust mathematical treatment of most of the arguments." (Ecoscience, June 2010)"Pastor (Univ. of Minnesota, Duluth) does an admirable job of bridging the gap, providing a work that should quickly become a popular choice for upper-level undergraduate or graduate courses in both disciplines." (CHOICE, January 2009)Table of ContentsPrologue. Preface. Acknowledgments. Part I: Preliminaries. 1. What is Mathematical Ecology and Why Should We Do It?. 2. Mathematical Toolbox. Part II: Populations. 3. Homogeneous Populations: Exponential and Geometric Growth and Decay. 4. Age- and Stage-structured Linear Models: Relaxing The Assumption Of Population Homogeneity. 5. Nonlinear Models of Single Populations: The Continuous Time Logistic Model. 6. Discrete Logistic Growth, Oscillations, and Chaos. 7. Harvesting and the Logistic Model. 8. Predators and their Prey. 9. Competition between Two Species, Mutualism, and Species Invasions. 10. Multispecies Community and Food Web Models. Part III: Ecosystems. 11. Inorganic Resources, Mass Balance, Resource Uptake, and Resource Use Efficiency. 12. Litter Return, Nutrient Cycling, and Ecosystem Stability. 13. Consumer Regulation of Nutrient Cycling. 14. Stoichiometry and Linked Element Cycles. Part IV: Populations and Ecosystems in Space and Time. 15. Transitions between Populations and States in Landscapes. 16. Diffusion, Advection, the Spread of Populations and Resources, and the Emergence of Spatial Patterns. Appendix: MatLab Commands for Equilibrium and Stability Analysis of Multi-compartment Models by Solving the Jacobian and its Eigenvalues. References. Index
£61.70
Society for Industrial & Applied Mathematics,U.S. Computing Highly Oscillatory Integrals
Book SynopsisHighly oscillatory phenomena range across numerous areas in science and engineering and their computation represents a difficult challenge. A case in point is integrals of rapidly oscillating functions in one or more variables. The quadrature of such integrals has been historically considered very demanding. Research in the past 15 years (in which the authors played a major role) resulted in a range of very effective and affordable algorithms for highly oscillatory quadrature. This is the only monograph bringing together the new body of ideas in this area in its entirety.The starting point is that approximations need to be analyzed using asymptotic methods rather than by more standard polynomial expansions. As often happens in computational mathematics, once a phenomenon is understood from a mathematical standpoint, effective algorithms follow. As reviewed in this monograph, we now have at our disposal a number of very effective quadrature methods for highly oscillatory integrals—Filon-type and Levin-type methods, methods based on steepest descent, and complex-valued Gaussian quadrature. Their understanding calls for a fairly varied mathematical toolbox—from classical numerical analysis, approximation theory, and theory of orthogonal polynomials all the way to asymptotic analysis—yet this understanding is the cornerstone of efficient algorithms.
£71.40
Society for Industrial & Applied Mathematics,U.S. Solitons in Two-Dimensional Shallow Water
Book SynopsisWeb-like waves, often observed on the surface of shallow water, are examples of nonlinear waves. They are generated by nonlinear interactions among several obliquely propagating solitary waves, also known as solitons. In this book, modern mathematical tools—algebraic geometry, algebraic combinatorics, and representation theory, among others—are used to analyze these two-dimensional wave patterns. The author’s primary goal is to explain some details of the classification problem of the soliton solutions of the KP equation (or KP solitons) and their applications to shallow water waves.This book is intended for researchers and graduate students.
£62.05
Society for Industrial & Applied Mathematics,U.S. Probability and Mathematical Statistics: Theory,
Book SynopsisThis book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data. Throughout the text, the R package is used to compute probabilities, check analytically computed answers, simulate probability distributions, illustrate answers with appropriate graphics, and help students develop intuition surrounding probability and statistics. Examples, demonstrations, and exercises in the R programming language serve to reinforce ideas and facilitate understanding and confidence. The book’s Chapter Highlights provide a summary of key concepts, while the examples utilizing R within the chapters are instructive and practical. Exercises that focus on real-world applications without sacrificing mathematical rigor are included, along with more than 200 figures that help clarify both concepts and applications. In addition, the book features two helpful appendices: annotated solutions to 700 exercises and a Review of Useful Math.
£95.20
Society for Industrial & Applied Mathematics,U.S. PETSc for Partial Differential Equations:
Book SynopsisThe Portable, Extensible Toolkit for Scientific Computation (PETSc) is an open-source library of advanced data structures and methods for solving linear and nonlinear equations and for managing discretizations. This book uses these modern numerical tools to demonstrate how to solve nonlinear partial differential equations (PDEs) in parallel. It starts from key mathematical concepts, such as Krylov space methods, preconditioning, multigrid, and Newton’s method. In PETSc these components are composed at run time into fast solvers.Discretizations are introduced from the beginning, with an emphasis on finite difference and finite element methodologies. The example C programs of the first 12 chapters, listed on the inside front cover, solve (mostly) elliptic and parabolic PDE problems. Discretization leads to large, sparse, and generally nonlinear systems of algebraic equations. For such problems, mathematical solver concepts are explained and illustrated through the examples, with sufficient context to speed further development. PETSc for Partial Differential Equations addresses both discretizations and fast solvers for PDEs, emphasizing practice more than theory. Well-structured examples lead to run-time choices that result in high solver performance and parallel scalability. The last two chapters build on the reader’s understanding of fast solver concepts when applying the Firedrake Python finite element solver library. This textbook, the first to cover PETSc programming for nonlinear PDEs, provides an on-ramp for graduate students and researchers to a major area of high-performance computing for science and engineering. It is suitable as a supplement for courses in scientific computing or numerical methods for differential equations.
£81.60
