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About this book
Are you a researcher or instructor who has been wanting to learn R and RStudio®, but you don?t know where to begin? Do you want to be able to perform all the same functions you use in IBM® SPSS® in R? Is your license to IBM® SPSS® expiring, or are you looking to provide your students guidance to a freely-available statistical software program?
Moving from IBM® SPSS® to R and RStudio®: A Statistics Companion is a concise and easy-to-read guide for users who want to know learn how to perform statistical calculations in R. Brief chapters start with a step-by-step introduction to R and RStudio, offering basic installation information and a summary of the differences. Subsequent chapters walk through differences between SPSS and R, in terms of data files, concepts, and structure. Detailed examples provide walk-throughs for different types of data conversions and transformations and their equivalent in R. Helpful and comprehensive appendices provide tables of each statistical transformation in R with its equivalent in SPSS and show what, if any, differences in assumptions factor to into each function. Statistical tests from t-tests to ANOVA through three-factor ANOVA and multiple regression and chi-square are covered in detail, showing each step in the process for both programs. By focusing just on R and eschewing detailed conversations about statistics, this brief guide gives adept SPSS® users just the information they need to transition their data analyses from SPSS to R.
Moving from IBM® SPSS® to R and RStudio®: A Statistics Companion is a concise and easy-to-read guide for users who want to know learn how to perform statistical calculations in R. Brief chapters start with a step-by-step introduction to R and RStudio, offering basic installation information and a summary of the differences. Subsequent chapters walk through differences between SPSS and R, in terms of data files, concepts, and structure. Detailed examples provide walk-throughs for different types of data conversions and transformations and their equivalent in R. Helpful and comprehensive appendices provide tables of each statistical transformation in R with its equivalent in SPSS and show what, if any, differences in assumptions factor to into each function. Statistical tests from t-tests to ANOVA through three-factor ANOVA and multiple regression and chi-square are covered in detail, showing each step in the process for both programs. By focusing just on R and eschewing detailed conversations about statistics, this brief guide gives adept SPSS® users just the information they need to transition their data analyses from SPSS to R.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Moving from IBM® SPSS® to R and RStudio® by Howard T. Tokunaga in PDF and/or ePUB format, as well as other popular books in Psychology & Computer Science General. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Acknowledgements
- Title Page
- Copyright Page
- Brief Contents
- Detailed Contents
- About the Author
- Acknowledgments
- Introduction
- 1 Introduction to R
- 2 Preparing to use R and RStudio
- 3 R terms, concepts, and command structure
- 4 Introduction to RStudio
- 5 Conducting RStudio sessions: A detailed example
- 6 Conducting RStudio sessions: A brief example
- 7 Conducting statistical analyses using this book: A detailed example
- 8 Conducting statistical analyses using this book: A brief example
- 9 Working with data frames and variables in R
- 10 Conducting statistical analyses using SPSS syntax
- Appendix A: Data Transformations
- Appendix B: Statistical procedures
- Further resources