Probability and statistics Books
Taylor & Francis Ltd Using Statistics to Understand the Environment Routledge Introductions to the Environment
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£37.99
Taylor & Francis Statistics for Sport and Exercise Studies
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£156.75
Taylor & Francis Ltd An Objective Theory Of Probability Routledge Revivals
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£51.29
Taylor & Francis Mathematics for Economists with Applications
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£175.75
Taylor & Francis Mathematics for Economists with Applications
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£99.75
Taylor & Francis Ltd A Primer of Multivariate Statistics
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£51.29
Taylor & Francis Ltd Latent Variable and Latent Structure Models
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£51.29
Taylor & Francis Ltd Modeling Intraindividual Variability With Repeated Measures Data
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£49.39
Taylor & Francis Ltd New Developments and Techniques in Structural Equation Modeling
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£41.59
Taylor & Francis MetaRegression Analysis in Economics and Business
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£142.50
Taylor & Francis The Meaning of the Concept of Probability in Application to Finite Sequences Routledge Revivals
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£45.59
Taylor & Francis The Meaning of the Concept of Probability in Application to Finite Sequences Routledge Revivals
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£32.99
Taylor & Francis Statistics for Business
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£175.75
Taylor & Francis Longitudinal Data Analysis
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£128.25
Taylor & Francis Longitudinal Data Analysis
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£51.29
Taylor & Francis Ltd Introductory Regression Analysis with Computer Application for Business and Economics
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£99.75
Taylor & Francis Introductory Regression Analysis with Computer Application for Business and Economics
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£73.14
Elsevier Science Essential Bayesian Models
Book SynopsisFocuses on key methodologies and applications for Bayesian models and computation. This book describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation.Table of Contents1. Model Selection and Hypothesis Testing based on Objective Probabilities and Bayes Factors; 2. Bayesian Model Checking and Model Diagnostics; 3. Bayesian Nonparametric Modeling and Data Analysis: An Introduction; 4. Some Bayesian Nonparametric Models; 5. Bayesian Modeling in the Wavelet Domain; 6. Bayesian Methods for Function Estimation; 7. MCMC Methods to Estimate Bayesian Parametric Models; 8. Bayesian Computation: From Posterior Densities to Bayes Factors, Marginal Likelihoods, and Posterior Model Probabilities; 9. Bayesian Modelling and Inference on Mixtures of Distributions; 10. Variable Selection and Covariance Selection in Multivariate Regression Models; 11. Dynamic Models; 12. Elliptical Measurement Error Models – A Bayesian Approach; 13. Bayesian Sensitivity Analysis in Skew-elliptical Models; 14. Bayesian Methods for DNA Microarray Data Analysis; 15. Bayesian Biostatistics; 16. Innovative Bayesian Methods for Biostatistics and Epidemiology; 17. Modeling and Analysis for Categorical Response Data; 18. Bayesian Methods and Simulation-Based Computation for Contingency Tables; 19. Teaching Bayesian Thought to Nonstatisticians
£53.99
Taylor & Francis Ltd The Doctrine of Chances A Method of Calculating the Probabilities of Events in Play Library of Science Classics
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£128.25
Taylor & Francis Applied Statistics for Public Policy
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£128.25
Taylor & Francis Advanced Structural Equation Modeling
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£128.25
Taylor & Francis What If There Were No Significance Tests Multivariate Applications Series
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£128.25
Taylor & Francis Structural Equation Modeling With Lisrel Prelis and Simplis
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£128.25
Taylor & Francis Levines Guide to SPSS for Analysis of Variance
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£80.74
Taylor & Francis Structural Equation Modeling With EQS
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£56.04
Taylor & Francis Structural Equation Modeling with Mplus Basic Concepts Applications and Programming Multivariate Applications Series
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£142.50
Taylor & Francis Introduction to Statistical Mediation Analysis
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£51.99
Taylor & Francis Applied DiscreteChoice Modelling
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£128.25
Taylor & Francis Applied DiscreteChoice Modelling
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£33.99
Taylor & Francis Introduction to Statistics in Human Performance
Introduction to Statistics in Human Performance | BookCurl
£128.25
Taylor & Francis Introduction to Statistics in Human Performance
Introduction to Statistics in Human Performance | BookCurl
£54.14
Taylor & Francis Ltd Elementary Statistics for Effective Library and Information Service Management
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£56.04
Taylor & Francis Ltd Handbook of Regression Modeling in People
Book SynopsisDespite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best swiss army knife' we have for answering these kinds of questions.This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a sweet spot' where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wTable of Contents1. The Importance of Regression in People Analytics. 2. The Basics of the R Programming Language. 3. Statistics Foundations. 4. Linear Regression for Continuous Outcomes. 5. Binomial Logistic Regression for Binary Outcomes. 6. Multinomial Logistic Regression for Nominal Category Outcomes. 7. Ordinal Logistic Regression for Ordered Category Outcomes. 8. Modeling Explicit and Latent Hierarchical Structure in Data. 9. Survival Analysis for Modeling the Occurrence of Singular Events Over Time. 10. Alternative Technical Approaches in R and Python. 11. Power Analysis to Estimate Required Sample Sizes for Inferential Modeling. 12. Further Exercises for Practice.
£68.99
Taylor & Francis Ltd Statistical Methods for Handling Incomplete Data
Book SynopsisDue to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data.Features Uses the mean score equation as a building block for developing the theory for missing data analysis Provides comprehensive coverage of computational techniques for missing data analysis Presents a rigorous treatment of imputation techniques, including multiple imputation fractional imputation Explores the most recent advances of the propensity score method and estimation techniques for nonignorable missing data Describes a survey sampling application Updated with a new chapter on Data Integration Now includes a chapter on Advanced Topics, including kernel ridge regression imputation and neural network model imputation The book is primarily aimed at researchers and graduate students from statistics, and could be used as a reference by applied researchers with a good quantitative background. It includes many real data examples and simulated examples to help readers understand the methodologies.Trade Review"As a general comment, I must say that it is probably one of the most extensive, detailed and complete sources of information on the most up-to-date methods to deal with missing data, from simple imputation methods to more complex analysis techniques that take missingness into account. The book is well organized in 12 chapters that although could be read independently based on the readers needs/interest, it does have a hierarchy that makes sense going from more simple early chapters to more complex subjects later in the book."~David Manteigas, ISCB Book ReviewsTable of Contents1. Introduction2. Likelihood-based Approach3. Computation4. Imputation5. Multiple Imputation6. Fractional Imputation7. Propensity Scoring Approach8. Nonignorable Missing Data9. Longitudinal and Clustered Data10. Application to Survey Sampling11. Data Integration12. Advanced Topics
£43.69
Taylor & Francis Ltd Multivariate Data Integration Using R
Book SynopsisLarge biological data, which are often noisy and high-dimensional, have become increasingly prevalent in biology and medicine. There is a real need for good training in statistics, from data exploration through to analysis and interpretation. This book provides an overview of statistical and dimension reduction methods for high-throughput biological data, with a specific focus on data integration. It starts with some biological background, key concepts underlying the multivariate methods, and then covers an array of methods implemented using the mixOmics package in R. Features: Provides a broad and accessible overview of methods for multi-omics data integration Covers a wide range of multivariate methods, each designed to answer specific biological questions Includes comprehensive visualisation techniques to aid in data interpretation Includes many worked examples and case studies using real data<Trade Review"This book was eagerly awaited both to bring together numerous research works published in recent years and to support the use of the Mixomics software which has become an essential tool for data integration and exploration when dealing with multiple types of high-dimensional biological data. It is the result of many years of research on cutting-edge developments in this domain as for sparsity. The book is very pleasant to read and well-structured around the different multivariate approaches. It is well documented with many recent references on the statistical methods and is very didactic through numerous examples accompanied by R codes and illustrations. It can be used by a large audience of statisticians and biologists to process, analyze, visualize, and interpret their multivariate microbiome and multi-omics data, but also as a basis for a course. I highly recommend this book."- Philippe Bastien, Senior Research Associate - L'Oréal R&I "The book belongs to the Computational Biology Series and presents a wide spectrum of modern methods of multivariate statistical analysis, integration and high-dimension reduction for biological data evaluated via the specialized R package. The neologism Omic is used as a root related to constellations of objects with biological information, for instance, in genomes and proteins—genomics and proteomics (in studying proteins expressed by cells and tissues), metabolic and transcription products—metabolomics and transcriptomics (in studying messenger RNA molecules expressed from the gens of an organism), or also in economics—Reaganomics, etc. [. . . ] Numerous links to the internet websites related to the considered methods of multi-omics data integration are suggested, particularly, the mixOmics project is described at the link http://www.mixOmics.org, and the package is available at Install |mixOmics. The developed methods and software are suitable not only for biologists and bioinformaticians students and researchers, but can be useful for solving computational and content problems in many other fields as well."– Technometrics "This is an excellent book for computational biologists, bioinformaticians, statisticians, data scientists, and graduate students who work with high-throughput omics data. The book covers most fundamental concepts of multi-omics data integration, while focusing on their implementations through hands-on examples implemented in the mixOmics R package."- Yuehua Cui, Michigan State University, Biometrics, September 2022 Table of ContentsI Modern biology and multivariate analysis 1. Multi-omics and biological systems2. The cycle of analysis3. Key multivariate concepts and dimension reduction in mixOmics4. Choose the right method for the right question in mixOmics II mixOmics under the hood 5. Projection to Latent Structures6. Visualisation for data integration7. Performance assessment in multivariate analyses III mixOmics in action 8. mixOmics: get started9. Principal Component Analysis (PCA)10. 10 Projection to Latent Structure (PLS)11. Canonical Correlation Analysis (CCA)12. PLS - Discriminant Analysis (PLS-DA)13. N − data integration14. P − data integration15. Glossary of Terms
£43.69
Taylor & Francis Ltd Bayesian Analysis with R for Drug Development
Book SynopsisDrug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development.Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems.Features Provides a single source of information on Bayesian statistics for drug development CoTable of ContentsBackground. Drug Research and Development. Basics of Bayesian analysis. Bayesian Estimation of Sample Size and Power. Pre-Clinical and Clinical Research. Pre-clinical efficacy study. Futility analysis. Phase 3 Clinical Trial. Chemistry, Manufacturing, and Control. Analytical method. Process Development. Bayesian Approach to Statistical Process Control.
£39.99
Taylor & Francis Ltd Wavelets from a Statistical Perspective
Book SynopsisWavelets from a Statistical Perspective offers a modern, 2nd generation look on wavelets, far beyond the rigid setting of the equispaced, dyadic wavelets in the early days. With the methods of this book, based on the lifting scheme, researchers can set up a wavelet or another multiresolution analysis adapted to their data, ranging from images to scattered data or other irregularly spaced observations. Whereas classical wavelets stand a bit apart from other nonparametric methods, this book adds a multiscale touch to your spline, kernel or local polynomial smoothing procedure, thereby extending its applicability to nonlinear, nonparametric processing for piecewise smooth data.One of the chapters of the book constructs B-spline wavelets on nonequispaced knots and multiscale local polynomial transforms. In another chapter, the link between wavelets and Fourier analysis, ubiquitous in the classical approach, is explained, but without being inevitable. In further chap
£42.74
Taylor & Francis Ltd Visualizing Surveys in R
Book SynopsisFor researchers who use surveys interested in learning how to seize vast possibilities and flexibility of R in survey analysis/visualizations. Psychologists, marketeers, HR personnel, managers, other professionals who wish to standardize/automate the process for visualizing survey data. Suitable for textbook courses.Table of ContentsI Preparation. 1. Survey data. 2. Process. 3. Variables. 4. Categories. 5. Read data. 6. Parse values. 7. Validate data. 8. Pre-process data. 9. Build a dataset. 10. Basic statistics. 11. Create plots with ggplot2. 12. Save plots to files. 13. R Markdown. II Plotting. 14. Numeric plots. 15. Bar charts. 16. Percentage bars. 17. Diverging percentage bars. 18. Pie charts. 19. Lollipop plots. 20. Dot plots. 21. Heatmaps. 22. Geographic maps. 23. Missing value plots. 24. Validation plots.
£137.75
Taylor & Francis Ltd Urban Informatics
Book SynopsisUrban Informatics: Using Big Data to Understand and Serve Communities introduces the reader to the tools of data management, analysis, and manipulation using R statistical software. Designed for undergraduate and above level courses, this book is an ideal onramp for the study of urban informatics and how to translate novel data sets into new insights and practical tools.The book follows a unique pedagogical approach developed by the author to enable students to build skills by pursuing projects that inspire and motivate them. Each chapter has an Exploratory Data Assignment that prompts readers to practice their new skills on a data set of their choice. These assignments guide readers through the process of becoming familiar with the contents of a novel data set and communicating meaningful insights from the data to others.Key Features: The technical curriculum consists of both data management and analytics, including both as needed to become acquainted with and reveal the content of a new data set. Content that is contextualized in real-world applications relevant to community concerns. Unit-level assignments that educators might use as midterms or otherwise. These include Community Experience assignments that prompt students to evaluate the assumptions they have made about their data against real world information. All data sets are publicly available through the Boston Data Portal. Table of Contents1 Introduction 2 Welcome to R 3 Telling a Data Story: Examining Individual Records 4 The Pulse of the City: Observing Variable Patterns 5 Uncovering Information: Making and Creating Variables 6 Measuring with Big Data 7 Making Measures from Records: Aggregating and Merging Data 8 Mapping Communities 9 Advanced Visual Techniques 10 Beyond Measurement: Inferential Statistics (and Correlations) 11 Identifying Inequities across Groups: ANOVA and t-Test 12 Unpacking Mechanisms Driving Inequities: Multivariate Regression 13 Advanced Analytic Techniques 14 Emergent Technologies
£123.50
Taylor & Francis Ltd Modern Data Visualization with R
£58.89
Taylor & Francis Ltd An Advanced Course in Probability and Stochastic
Book SynopsisAn Advanced Course in Probability and Stochastic Processes provides a modern and rigorous treatment of probability theory and stochastic processes at an upper undergraduate and graduate level. Starting with the foundations of measure theory, this book introduces the key concepts of probability theory in an accessible way, providing full proofs and extensive examples and illustrations. Fundamental stochastic processes such as Gaussian processes, Poisson random measures, Lévy processes, Markov processes, and Itô processes are presented and explored in considerable depth, showcasing their many interconnections. Special attention is paid to martingales and the Wiener process and their central role in the treatment of stochastic integrals and stochastic calculus. This book includes many exercises, designed to test and challenge the reader and expand their skillset. An Advanced Course in Probability and Stochastic Processes is meant for students and researchers who have a soTable of Contents1. Measure Theory 2. Probability 3. Convergence 4. Conditioning 5. Martingales 6. Wiener and Brownian Motion Processes 7. Itô Calculus Appendix A. Selected Solutions Appendix B. Function Spaces Appendix C. Existence of the Lebesgue Measure Index
£111.89
Taylor & Francis Ltd Exploring Data Science with R and the Tidyverse
Book SynopsisThis book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows without needing to reference extensive amounts of external resources for onboarding. The contents are targeted for undergraduate students but are equally applicable to students at the graduate level and beyond. The book develops concepts using many real-world examples to motivate the reader. Upon completion of the text, the reader will be able to: Gain proficiency in R programming Load and manipulate data frames, and tidy them using tidyverse tools Conduct statistical analyses and draw meaningful inferences from them Perform modeling from numerical and textual data Generate data visualizations (numerical and spatialTable of Contents1. Data Types 2. Data Transformation 3. Data Visualization 4. Building Simulations 5. Sampling 6. Hypothesis Testing 7. Quantifying Uncertainty 8. Towards Normality 9. Regression 10. Text Analysis
£73.14
Taylor & Francis Ltd Introducing Financial Mathematics
Book SynopsisIntroducing Financial Mathematics: Theory, Binomial Models, and Applications seeks to replace existing books with a rigorous stand-alone text that covers fewer examples in greater detail with more proofs. The book uses the fundamental theorem of asset pricing as an introduction to linear algebra and convex analysis. It also provides example computer programs, mainly Octave/MATLAB functions but also spreadsheets and Macsyma scripts, with which students may experiment on real data.The text''s unique coverage is in its contemporary combination of discrete and continuous models to compute implied volatility and fit models to market data. The goal is to bridge the large gaps among nonmathematical finance texts, purely theoretical economics texts, and specific software-focused engineering texts.Table of ContentsPreface 1. Basics 2. Continuous Models 3. Discrete Models 4. Exotic Models 5. Forwards and Futures 6. Dividends and Interest 7. Implied Volatility 8. Fundamental Theorems Project Suggestions Answers and Index
£73.14
Taylor & Francis Ltd Tidy Finance with R
Book SynopsisThis textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the tidyverse family of R packages. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.HigTable of Contents1. Introduction to Tidy Finance 2. Accessing & Managing Financial Data 3. WRDS, CRSP, and Compustat 4. TRACE and FISD 5. Other Data Providers 6. Beta Estimation 7. Univariate Portfolio Sorts 8. Size Sorts and P-Hacking 9. Value and Bivariate Sorts 10. Replicating Fama and French Factors 11. Fama-MacBeth Regressions 12. Fixed Effects and Clustered Standard Errors 13. Difference in Differences 14. Factor Selection via Machine Learning 15. Option Pricing via Machine Learning 16. Parametric Portfolio Policies 17. Constrained Optimization and Backtesting Appendix A. Cover Design Appendix B. Clean Enhanced TRACE with R
£61.99
Taylor & Francis Ltd Mathematical Conundrums
Book SynopsisWant to sharpen your mathematical wits? If so, then Mathematical Conundrums is for you. Daily Telegraph enigmatologist, Barry R. Clarke, presents over 120 fiendish problems that will test both your ingenuity and persistence. Between these covers are puzzles in geometry, arithmetic, and algebra (there is even a section for computer programmers). And, for the smartest readers who wish to stretch their mind to its limits, a selection of engaging logic and visual lateral puzzles is included. Although no puzzle requires a greater knowledge of mathematics than the high school curriculum, this collection will take you to the edge. But are you equal to the challenge? Features High-school level of mathematics is the only pre-requisite Variety of algebraic, route-drawing, and geometrical conundrums Hints section for the lateral puzzles Warm-up excercises to sharpen the wits Full solutions to every problem Barry R. Clarke has published over 1,500 puzzles in The Daily Telegraph and has contributed enigmas to New Scientist, The Sunday Times, Readerâs Digest, The Sunday Telegraph, and Prospect magazine. His book Challenging Logic Puzzles Mensa has sold over 100,000 copies. As well as a PhD in Shakespeare Studies, Barry has a masterâs degree and academic publications in quantum physics. He is now working on a revised theory of the hydrogen atom. Other skills include mathematics tutor, filmmaker, comedy-sketch writer, cartoonist, computer programmer, and blues guitarist! For more information please visit http://barryispuzzled.com.Table of Contents1. Introduction. 2. Mind sharpeners. 3. Geometry. 4. Arithmetic. 5. Algebra. 6. Programmable Puzzles. 7. Logic. 8. Visual-lateral
£23.99
Taylor & Francis The Craft of Political Research
Book Synopsis
£62.69
Taylor & Francis Ltd Applying the Rasch Model and Structural Equation
Book SynopsisThis book introduces the fundamentals of the technology satisfaction model (TSM), supporting readers in applying the Rasch model and structural equation modeling (SEM) a multivariate technique to higher education (HE) research. User satisfaction is traditionally measured along a single dimension. However, the TSM includes digital technologies for teaching, learning and research across three dimensions: computer efficacy, perceived ease of use and perceived usefulness. Establishing relationships among these factors is a challenge. Although commonly used in psychology to trace relationships, Rasch and SEM approaches are rarely used in educational technology or library and information science. This book, therefore, shows that combining these two analytical tools offers researchers better options for measurement and generalisation in HE research. This title presents theoretical and methodological insights of use to researchers in HE.Table of Contents1. Assessment of ICT in Higher Education Applying the TSM. 2. Testing Online Learning Satisfaction in Higher Education. 3. Assessing Online Research Databases in Higher Education Using the TSM. 4. Measurement of Wireless Internet in Higher Education Using the TSM.
£87.39
Taylor & Francis Ltd Numerical Techniques in MATLAB
Book SynopsisIn this book, various numerical methods are discussed in a comprehensive way. It delivers a mixture of theory, examples and MATLAB practicing exercises to help the students in improving their skills. To understand the MATLAB programming in a friendly style, the examples are solved. The MATLAB codes are mentioned in the end of each topic. Throughout the text, a balance between theory, examples and programming is maintained.Key Features Methods are explained with examples and codes System of equations has given full consideration Use of MATLAB is learnt for every method This book is suitable for graduate students in mathematics, computer science and engineering.Table of Contents1. Common Commands Used in Matlab. 2. System of Linear Equations. 3. Polynomial Interpolation. 4. Root Finding Methods. 5. Numerical Integration. 6. Solution of Initial Value Problems. 7. Boundary Value Problems.
£87.39