Practical Statistics in R — Comparing Groups: Numerical Variables

front-cover r-statistics-for-comparing-means What you will learn Key features of this book How this book is organized ? Book website Executing the R codes from the PDF Acknowledgment Colophon About the author Introduction to R Install R and RStudio Install and load required R packages Data format Import your data in R Demo data sets Data manipulation Close your R/RStudio session I Statistical Tests and Assumptions Introduction Research questions and statistics Assumptions of statistical tests Assessing normality Assessing equality of variances Summary Assessing Normality Introduction Prerequisites Demo data Examples of distribution shapes Check normality in R Summary Homogeneity of Variance Introduction Prerequisites F-test: Compare two variances Compare multiple variances Summary Mauchly's Test of Sphericity Introduction Prerequisites Demo data Measuring sphericity Computing ANOVA and Mauchly's test Interpreting ANOVA results Choosing sphericity corrections methods ANOVA table Summary Transforming Data to Normality Introduction Non-normal distributions Transformation methods Examples of transforming skewed data Summary and discussion II Comparing Two Means Introduction T-test Introduction Prerequisites One-Sample t-test Independent samples t-test Paired samples t-test Summary Wilcoxon Test Introduction Prerequisites One-sample Wilcoxon signed rank test Wilcoxon rank sum test Wilcoxon signed rank test on paired samples Summary Sign Test Introduction Prerequisites Demo dataset Statistical hypotheses Summary statistics Visualization Computation Report Summary III Comparing Multiple Means Introduction R functions and packages Recommendations ANOVA - Analysis of Variance Introduction Basics Assumptions Prerequisites One-way ANOVA Two-way ANOVA Three-Way ANOVA Summary Repeated measures ANOVA Introduction Assumptions Prerequisites One-way repeated measures ANOVA Two-way repeated measures ANOVA Three-way repeated measures ANOVA Summary Mixed ANOVA Introduction Assumptions Prerequisites Two-way mixed ANOVA Three-way mixed ANOVA: 2 between- and 1 within-subjects factors Three-way Mixed ANOVA: 1 between- and 2 within-subjects factors Summary ANCOVA: Analysis of Covariance Introduction Assumptions Prerequisites One-way ANCOVA Two-way ANCOVA Summary One-Way MANOVA Introduction Prerequisites Data preparation Visualization Summary statistics Assumptions and preleminary tests Computation Post-hoc tests Report Summary Kruskal-Wallis Test Introduction Prerequisites Data preparation summary statistics Visualization Computation Effect size Multiple pairwise-comparisons Report Friedman Test Introduction Prerequisites Data preparation Summary statistics Visualization Computation Effect size Multiple pairwise-comparisons Report