Understanding Statistics Using R

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.