ABSTRACT
This chapter provides a hands-on introduction to using data analytics in R for traditional social science statistical procedures. The Companion Website (www.routledge.com/9780367624293) to this books provides all needed data used as examples. Statistical procedures and topic presented with worked examples in this chapter include descriptive statistics, linear multiple regression, hypothesis testing (one-sample means tests, means tests for two independent samples, means tests for two dependent samples), crosstabulation with tests of significance and measures of association, loglinear analysis of categorical variable, correlation with correlograms and scatterplots, exploratory factor analysis, multidimensional scaling, reliability analysis (Cronbach's alpha, Guttman's lower bounds, Krippendorff's alpha, Cohen’t kappa), cluster analysis (hierarchical, k-means, and nearest-neighbor), the Anova family (Anova, Ancova, Manova, Mancova), logistic regression with discussion of ROC curves and confusion tables, and mediation and moderation analysis.
