Understanding Statistics Using R

• Main Authors: Schumacker, Randall. (Author), Tomek, Sara. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2013.
• Subjects: Computer science.; Computer simulation.; Computer Science.; Probability and Statistics in Computer Science.; Simulation and Modeling.; Models and Principles.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-6227-9

 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������