1st Edition

The R Student Companion

By Brian Dennis Copyright 2013
    360 Pages 58 B/W Illustrations
    by Chapman & Hall

    360 Pages
    by Chapman & Hall

    R is the amazing, free, open-access software package for scientific graphs and calculations used by scientists worldwide. The R Student Companion is a student-oriented manual describing how to use R in high school and college science and mathematics courses. Written for beginners in scientific computation, the book assumes the reader has just some high school algebra and has no computer programming background.

    The author presents applications drawn from all sciences and social sciences and includes the most often used features of R in an appendix. In addition, each chapter provides a set of computational challenges: exercises in R calculations that are designed to be performed alone or in groups.

    Several of the chapters explore algebra concepts that are highly useful in scientific applications, such as quadratic equations, systems of linear equations, trigonometric functions, and exponential functions. Each chapter provides an instructional review of the algebra concept, followed by a hands-on guide to performing calculations and graphing in R.

    R is intuitive, even fun. Fantastic, publication-quality graphs of data, equations, or both can be produced with little effort. By integrating mathematical computation and scientific illustration early in a student’s development, R use can enhance one's understanding of even the most difficult scientific concepts. While R has gained a strong reputation as a package for statistical analysis, The R Student Companion approaches R more completely as a comprehensive tool for scientific computing and graphing.

    Introduction: Getting Started with R
    R Tutorial
    Vectors
    Graphs
    Real-World Example
    Final Remarks
    Computational Challenges
    References

    R Scripts
    Creating and Saving an R Script
    Running an R Script
    Finding Errors in an R Script
    Sharpening Up Your Scripts with Comments
    Real-World Example
    Final Remarks
    Computational Challenges
    Reference

    Functions
    Creating New Functions in R
    More about User-Defined R Functions
    Real-World Example
    Final Remarks
    Computational Challenges
    Afternotes (Short Remarks on Topics for Further Study)
    References

    Basic Graphs
    Real-World Example
    Graphs of One Variable
    Graphs of Two Variables
    Final Remarks
    Computational Challenges
    Afternotes

    Data Input and Output
    Data Frames in R
    Final Remarks
    Computational Challenges
    Afternotes

    Loops
    Writing a "For-Loop"
    Checking the Loop
    OK, Mr. Fibonacci…So What?
    Real-World Example
    Final Remarks
    Computational Challenges
    References

    Logic and Control
    Logical Comparison Operators and Logical Vectors
    Boolean Operations
    Missing Data
    More about Indexes
    Conditional Statements
    Real-World Example
    Final Remarks
    Computational Challenges
    Afternotes
    Reference

    Quadratic Functions
    Real-World Example
    Final Remarks
    Computational Challenges
    References

    Trigonometric Functions
    Right Triangles
    Trigonometric Functions
    Right Triangles, Circles, and Radians
    Properties of Trigonometric Functions
    Polar Coordinates
    Triangulation of Distances
    Real-World Examples
    Final Remarks
    Computational Challenges
    Afternotes

    Exponential and Logarithmic Functions
    Achieving Real Power
    The Special Number e
    The Number e in Applications
    The Exponential Function
    Exponential Growth
    Logarithmic Functions
    Logarithmic Scales
    Real-World Examples
    Final Remarks
    Computational and Algebraic Challenges
    References

    Matrix Arithmetic
    Another Way to Multiply Vectors
    Matrix Multiplication
    Matrix Addition and Subtraction
    Reading a Data File into a Matrix
    Real-World Example
    Final Remarks
    Computational Challenges
    Afterwords
    References

    Systems of Linear Equations
    Matrix Representation
    Matrix Inverse
    Inverse Matrices and System Solutions in R
    Real-World Examples
    Final Remarks
    Computational Challenges
    Afternotes
    References

    Advanced Graphs
    Two-Dimensional Plots
    Options for Styles of Symbols, Lines, Axes
    Other Customizations
    Multiple Panels
    Three-Dimensional Plots
    Color
    Final Remarks
    Computational Challenges
    Reference

    Probability and Simulation
    Random Variables
    Probability
    Probability Distributions of Counts
    Probability Distributions of Measurements
    Real-World Example
    Computational Challenges
    Afternotes
    References

    Fitting Models to Data
    Fitting a Quadratic Model
    Multiple Predictor Variables
    Nonlinear Statistical Models
    Final Remarks
    Computational Challenges
    Afternotes
    References

    Conclusion—It Doesn’t Take a Rocket Scientist
    Real Solar System Example
    The Problem
    The Concept
    Changes in Velocities
    Move the Earth
    Getting Organized
    Outline of R Script for Calculating the Trajectory of Earth
    The R Script
    Computational Challenges
    Afternotes

    Appendix A: Installing R
    Appendix B: Getting Help
    Appendix C: Common R Expressions
    Index

    Biography

    Brian Dennis is a professor with a joint appointment in the Department of Fish and Wildlife Sciences and the Department of Statistical Sciences at the University of Idaho. He received a master's degree in statistics and a Ph.D. in ecology from The Pennsylvania State University. He has authored over 70 scientific articles on applications of statistics and mathematical modeling in ecology and natural resource management. He has been enthusiastically using R in his scientific work and teaching R in his courses for a decade.

    "… a good book for high school or college students wanting to learn R on their own. Complete mathematical explanations paired with computational examples in R provide an excellent tool for these students to obtain a solid foundation in R."
    —Erin R. Leatherman, The American Statistician, November 2014

    "One of the positive features of this book is its fearlessness. The message is that you are never too young to learn R (the book is aimed at high school and college students) and that the best way to learn is to jump straight into writing R expressions. The author’s enthusiasm for tackling challenges head on also shines off the page. … I am also in favour of the hands-on approach of the book; it is clearly written to be read while sitting at a keyboard. … The problem-based style of the book is another plus, where learning is motivated by first setting up an interesting question to answer. … a lively and interesting introduction to R. It furnishes a lot of useful material for introducing a very powerful tool to enquiring young minds."
    —Paul Murrell, Australian & New Zealand Journal of Statistics, 2014

    "This book requires no prior knowledge of calculus, programming, or statistics. … the commands and real-world examples are explained very thoroughly. This should make the book suitable for self-study and hold interest for the target group (high school and college-level students) …"
    —Joonas Kauppinen, International Statistical Review (2013), 81, 2

    "An R book for high schoolers! This is an excellent idea, and the quality of the product is equally excellent. It may be suitable for non-calculus-based introductory courses at the college level as well. … Dennis does a good job dispelling the ‘steep learning curve’ myth concerning R … . The writing style is clear and lively, and the examples should appeal to high school students. It is high time that introductory statistics be taught in an engaging manner that reflects our own enthusiasm for the subject, with meaningful data sets, attractive graphics, and so on. Dennis’ book is a fine contribution toward that goal."
    —Norman Matloff, Journal of Statistical Software, Volume 52, February 2013

    "What do you get out of Dennis’s book? You learn how to install R and add-on packages. You learn the basic syntax and discover how to make plots and do basic computations using R. A reader of this book will learn how to do some essential programming in R, and also see it applied to solve interesting example of real scientific problems. Indeed, The R Student Companion makes picking up R quick and easy."
    —Jason Graham, MAA Reveiws