Understanding Statistics Using R

  • Randall Schumacker
  • Sara Tomek

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Randall Schumacker, Sara Tomek
    Pages 1-10
  3. Randall Schumacker, Sara Tomek
    Pages 11-41
  4. Randall Schumacker, Sara Tomek
    Pages 43-53
  5. Randall Schumacker, Sara Tomek
    Pages 55-73
  6. Randall Schumacker, Sara Tomek
    Pages 75-105
  7. Randall Schumacker, Sara Tomek
    Pages 107-136
  8. Randall Schumacker, Sara Tomek
    Pages 137-168
  9. Randall Schumacker, Sara Tomek
    Pages 169-175
  10. Randall Schumacker, Sara Tomek
    Pages 177-186
  11. Randall Schumacker, Sara Tomek
    Pages 187-195
  12. Randall Schumacker, Sara Tomek
    Pages 197-207
  13. Randall Schumacker, Sara Tomek
    Pages 209-218
  14. Randall Schumacker, Sara Tomek
    Pages 219-228
  15. Randall Schumacker, Sara Tomek
    Pages 229-245
  16. Randall Schumacker, Sara Tomek
    Pages 247-261
  17. Back Matter
    Pages 263-289

About this book

Introduction

This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class.  The  chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials.  The book contains R script programs to demonstrate important topics and concepts covered in a statistics course, including probability, random sampling, population distribution types, role of the Central Limit Theorem, creation of sampling distributions for statistics, and more.  The chapters contain T/F quizzes to test basic knowledge of the topics covered.  In addition, the book chapters contain numerous exercises with answers or solutions to the exercises provided.  The chapter exercises reinforce an understanding of the statistical concepts presented in the chapters.  An instructor can select any of the supplemental materials to enhance lectures and/or provide additional coverage of concepts and topics in their statistics book.

This book uses the R statistical package which contains an extensive library of functions.  The R software is free and easily downloaded and installed.  The R programs are run in the R Studio software which is a graphical user interface for Windows. The R Studio software makes accessing R programs, viewing output from the exercises, and graphical displays easier to manage.  The first chapter of the book covers the fundamentals of the R statistical package.  This includes installation of R and R Studio, accessing R packages and libraries of functions.  The chapter also covers how to access manuals and technical documentation, as well as, basic R commands used in the R script programs in the chapters.  This chapter is important for the instructor to master so that the software can be installed and the R script programs run.  The R software is free so students can also install the software and run the R script programs in the chapters.   Teachers and students can run the R software on university computers, at home, or on laptop computers making it more available than many commercial software packages.

 

"As a professor who teaches research methods and advises master and doctoral students, I am often seeking practical resource materials that students can use in their research.  This book provides easy to run R examples that allow students to pick and choose content that is relevant to their research. When students learn that the cost for running R is free, they are especially happy!"

 

- Kim Nimon, University of North Texas  

 

"The authors have done a great job of providing resource materials an instructor can use when teaching a statistics course.  Strengths of the book are the inclusion of R code, the addition of more than 60 script programs, and the online exercise materials for students.  This book reflects the growing use of the mobile R software program for students who may not always have access to other statistical software packages housed on computers in a campus-based lab."

- David Walker, Northern Illinois University      

Keywords

Central Limiit Theorem Distribution Probability R Software Random Sampling Statistical Simulation Statistics

Authors and affiliations

  • Randall Schumacker
    • 1
  • Sara Tomek
    • 2
  1. 1.University of AlabamaTuscaloosaUSA
  2. 2.University of AlabamaTuscaloosaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-6227-9
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-6226-2
  • Online ISBN 978-1-4614-6227-9
  • About this book