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Full Description
Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioral, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter. This textbook is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods.
Contents
1. Introduction; 2. Examining Univariate Distributions; 3. Measures of Location, Spread, and Skewness; 4. Re-Expressing Variables; 5. Exploring Relationships between Two Variables; 6. Simple Linear Regression; 7. Probability Fundamentals; 8. Theoretical Probability Models; 9. The Role of Sampling in Inferential Statistics; 10. Inferences Involving the Mean of a Single Population when Σ is Known; 11. Inferences Involving the Mean When Σ is Not Known: One- and Two-Sample Designs; 12. Research Design: Introduction and Overview; 13. One-Way Analysis of Variance; 14. Two-Way Analysis of Variance; 15. Correlation and Simple Regression as Inferential Techniques; 16. An Introduction to Multiple Regression; 17. Two-Way Interactions in Multiple Regression; 18. Nonparametric Methods; 19. Accessing Data from Public Use Sources.
