A Guide to R for Social and Behavioral Science Statistics
eBook - ePub

A Guide to R for Social and Behavioral Science Statistics

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

A Guide to R for Social and Behavioral Science Statistics

About this book

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate students, shown in the R statistical language using RStudio®. The book is geared toward social and behavioral science statistics students, especially those with no background in computer science. Written as a companion book to be used alongside a larger introductory statistics text, the text follows the most common progression of statistics for social scientists. The guide also serves as a companion for conducting data analysis in a research methods course or as a stand-alone R and statistics text. This guide can teach anyone how to use R to analyze data, and uses frequent reminders of basic statistical concepts to accompany instructions in R to help walk students through the basics of learning how to use R for statistics. 

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Yes, you can access A Guide to R for Social and Behavioral Science Statistics by Brian Joseph Gillespie,Kathleen Charli Hibbert,William E. Wagner, III,William E. Wagner-Huang in PDF and/or ePUB format, as well as other popular books in Social Sciences & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Acknowledgements
  4. Title Page
  5. Copyright Page
  6. Brief Contents
  7. Detailed Contents
  8. Preface
  9. Acknowledgments
  10. About the Authors
  11. 1 R and RStudio®
  12. 2 Data, Variables, and Data Management
  13. 3 Data Frequencies and Distributions
  14. 4 Central Tendency and Variability
  15. 5 Creating and Interpreting Univariate and Bivariate Data Visualizations
  16. 6 Conceptual Overview of Hypothesis Testing and Effect Size
  17. 7 Relationships Between Categorical Variables
  18. 8 Comparing One or Two Means
  19. 9 Comparing Means Across Three or More Groups (ANOVA)
  20. 10 Correlation and Bivariate Regression
  21. 11 Multiple Regression
  22. 12 Advanced Regression Topics
  23. Index