Basic Statistical Analyses using R
What are normal data? What are non-normal data? How do you tell them apart and how do you know what sort of data you have? Chapter 5 begins teaching statistical analysis with a focus on understanding the shape of one’s data and how to measure it. The RxP dataset is explored and the principal focus in this chapter is on normal data and on conducting an Analysis of Variance (ANOVA), although classic non-parametric statistics such as a Kruskal-Wallis test and Mann-Whitney U test are also introduced. Readers are taught how to test for data normality, assess model fit, interpret the summary output from the model, calculate summary statistics and p-values, and how to conduct post-hoc tests (Tukey’s HSD) to compare different levels of a single predictor.