An R Companion for Applied Statistics I
eBook - ePub

An R Companion for Applied Statistics I

Basic Bivariate Techniques

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

An R Companion for Applied Statistics I

Basic Bivariate Techniques

About this book

An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner?s Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.

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Yes, you can access An R Companion for Applied Statistics I by Danney Rasco in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. 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. Acknowledgements
  10. Acknowledgments
  11. About the Author
  12. Chapter 1 Introduction: What Is R?
  13. Chapter 2 Basic Tasks in R
  14. Chapter 3 Frequency Tables
  15. Chapter 4 Descriptive Statistics
  16. Chapter 5 Visualizing Data: Bar Charts, Histograms, and Boxplots
  17. Chapter 6 Evaluating Score Locations: Introducing the Normal Distribution and z Scores
  18. Chapter 7 Sampling Error and Confidence Intervals
  19. Chapter 8 One-Sample t Test: Introduction to Statistical Significance Tests
  20. Chapter 9 Significance Tests Continued: Effect Size and Power
  21. Chapter 10 Bivariate Pearson Correlation
  22. Chapter 11 Bivariate Regression
  23. Chapter 12 Independent-Samples t Test
  24. Chapter 13 One-Way Between-Subjects Analysis of Variance
  25. Chapter 14 Paired-Samples t Test
  26. Chapter 15 One-Way Repeated-Measures Analysis of Variance
  27. Chapter 16 Factorial Analysis of Variance
  28. Chapter 17 Chi-Square (χ2) Test of Independence
  29. Chapter 18 Parting Thoughts About R
  30. References