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Foundations and Applications of Statistics: An Introduction Using R
Randall Pruim
Price : ₹ 1320.00
ISBN : 978-1-4704-2577-7
Language : English
Pages : 640
Binding : Paperback
Book Size : 180 x 240 mm
Year : 2016
Series : American Mathematical Society
Territorial Rights : Restricted
Imprint : No Image
About the Book

This book simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students’ practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students’ mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. This book discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. It contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations.

Table of Contents

Chapter 1. Summarizing Data  
Chapter 2. Probability and Random Variables 
Chapter 3. Continuous Distributions 
Chapter 4. Parameter Estimation and Testing 
Chapter 5. Likelihood-based Statistics 
Chapter 6. Introduction to Linear Models 
Chapter 7. More Linear Models 
Appendix A. A Brief Introduction to R 
Appendix B. Some Mathematical Preliminaries 
Appendix C. Geometry and Linear Algebra Review 
Appendix D. Review of Chapters 1–4 
Index to R Functions, Packages, and Data Sets 

Contributors (Author(s), Editor(s), Translator(s), Illustrator(s) etc.)

Randall Pruim is Professor and Chair of the Department of Mathematics and Statistics, Calvin College, Grand Rapids, USA

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