Discription

This book teaches statistics in a cheerful, straightforward manner, using the R open source programming language. Without mathematical formulae, the book assumes no knowledge of coding or statistics. Yet the lucid writing and clear structure takes the reader quickly and logically from beginner to graduate level. All tests come with worked examples. Tests include t tests, Mann-Whitney and Wilcoxon; one-way ANOVA, Kruskal-Wallis and Friedman; correlations and regression; categorical analyses including binomial, goodness of fit, chi square test of association, log-linear regression and McNemar; factorial ANOVA; MANOVA; principal components analysis and factor analysis; cluster analysis; logistic regression; the Kaplan-Meier curve and follow-up life tables; partial correlations, including non-parametric; an introduction to Bayesian statistics. The book takes a consistent approach to effect sizes, as well as covering data assumptions and confidence intervals. This should appeal to students, academics and professionals.