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Foundations and Applications of Statistics: An Introduction Using $\mathsf{R}$
 
Randall Pruim Calvin College, Grand Rapids, MI
Front Cover for Foundations and Applications of Statistics
Now available in new edition: AMSTEXT/28
Front Cover for Foundations and Applications of Statistics
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  • Front Cover for Foundations and Applications of Statistics
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Foundations and Applications of Statistics: An Introduction Using $\mathsf{R}$
Randall Pruim Calvin College, Grand Rapids, MI
Now available in new edition: AMSTEXT/28
  • Book Details
     
     
    Pure and Applied Undergraduate Texts
    Volume: 132011; 615 pp
    MSC: Primary 62; Secondary 60;

    Now available in Second Edition: AMSTEXT/28

    Foundations and Applications of Statistics 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 \(\mathsf{R}\) 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.

    Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book 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.

    Readership

    Undergraduate students interested in statistics.

  • Table of Contents
     
     
    • Cover
    • Title page
    • Contents
    • Preface
    • What is statistics?
    • Summarizing data
    • Probability and random variables
    • Continuous distributions
    • Parameter estimation and testing
    • Likelihood-based statistics
    • Introduction to linear models
    • More linear models
    • A brief introduction to R
    • Some mathematical preliminaries
    • Geometry and linear algebra review
    • Review of Chapters 1–4
    • Hints, answers, and solutions to selected exercises
    • Bibliography
    • Index to R functions, packages, and data sets
    • Index
    • Back Cover
  • Get Permissions
Volume: 132011; 615 pp
MSC: Primary 62; Secondary 60;

Now available in Second Edition: AMSTEXT/28

Foundations and Applications of Statistics 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 \(\mathsf{R}\) 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.

Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book 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.

Readership

Undergraduate students interested in statistics.

  • Cover
  • Title page
  • Contents
  • Preface
  • What is statistics?
  • Summarizing data
  • Probability and random variables
  • Continuous distributions
  • Parameter estimation and testing
  • Likelihood-based statistics
  • Introduction to linear models
  • More linear models
  • A brief introduction to R
  • Some mathematical preliminaries
  • Geometry and linear algebra review
  • Review of Chapters 1–4
  • Hints, answers, and solutions to selected exercises
  • Bibliography
  • Index to R functions, packages, and data sets
  • Index
  • Back Cover
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