This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without programming. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user and easier to use for the experienced user.
Highlights of the book include:
Quick Starts that introduce readers to the concepts and commands reviewed in the chapters.
Margin notes that highlight,define,illustrate,and cross-reference the key concepts.When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction.
Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output.
Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate how to interpret results.
Two data sets provided on the website and analyzed multiple times in the book, provide continuity throughout.
End of chapter worked problems help readers test their understanding of the concepts.
A website at www.lessRstats.com that features the lessR program, the book’s data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book’s worked problems, links to R/lessR videos to help readers better understand the program, and more.
An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used, taught in departments of psychology, business, education, and other social and health sciences, this book is also appreciated by researchers interested in using R for their data analysis. Prerequisites include basic statistical knowledge. Knowledge of R is not assumed.
Table of Contents
1. R for Data Analysis 2. Read/Write Data 3. Edit Data 4. Categorical Variables 5. Continuous Variables 6. Means, Compare Two Samples 7. Compare Multiple Samples 8. Correlation 9. Regression I 10. Regression II 11. Factor/Item Analysis
David W. Gerbing is a Professor in the School of Business Administration at Portland State University. He has published extensively in psychology, sociology, education, statistics, and business.
"R requires a steep learning curve to master. Gerbing’s book flattens that learning curve significantly. The breadth of the topics covered, the helpful worked examples, and the ability to move beyond the subject matter covered to other R applications renders this volume of immense value to researchers and provides an excellent text for graduate statistics courses."-Frank Boster, Michigan State University, USA
"This book is a straightforward resource for students or data analysts who would like to use R without investing valuable time learning the minutia associated with programming in R. David Gerbing makes an intimidating programming language manageable with examples from real-world scenarios. What sets this book apart is the depth and approachable level in which the output is explained."-Tiffany A. Whittaker, The University of Texas at Austin, USA
"My interest in this book was piqued by two features: it uses the computer system R and it seeks to make the system more accessible to data analysts. I have migrated all of my courses to R, and any effort to make R more accessible is to be commended. A quick scan of some sample chapters indicates that the material is attractively presented; this book deserves a serious look from instructors of applied statistics courses."-William B. Ware, University of North Carolina at Chapel Hill, USA
"The book in combination with the lessR package has the potential to lower the bar in terms of initial learning required for working with R. ...The combination of lessR with the ... book is like an "R for dummies". ... lessR. ... It will appeal to users who were ... intimidated by R’s complexity. ... I would recommend it to my students and could imagine building an introductory course around it."–Bertolt Meyer, University of Zurich, Switzerland
"The book makes a significant contribution to the field. It makes statistics and R available to more people. ... LessR is a very useful package. ... I was able to test some of the functions presented on my own data set and it worked well. ... The author developed a very nice and easy package. ... The book... make[s] using R easier. ... I would ... recommend it to my friends who want to start programming in R ... [and] for my ... course that ... uses R."–Agnieszka Kwapisz, Montana State University, USA
"I would use the book as a supplement ... in my introduction to ... statistics course ... [and] recommend it to all graduate students as a good way to teach themselves R. ... The strength of the book is the lessR package and the examples of how to call the functions in the package. ... The book could be an important contribution to the use of R in teaching statistics."–J. Patrick Gray, University of Wisconsin – Milwaukee, USA