Hypothesis Tests and Exploratory Analysis Using R Commander and Factoshiny

An understanding of statistical concepts is necessary for a chemist with a complete education. Here, statistical tests were taught using the R Commander and the Factoshiny packages. These packages run on R software and have a graphical user interface (GUI), which allows students to do statistical tests quickly and easily. These packages were presented through 14 case studies. In each case study, a data set was provided in MS Excel format, and a series of questions were answered using these packages. Hypothesis tests and exploratory analysis (principal component analysis; PCA) were taught using R Commander and Factoshiny, respectively. Outlier results were found using boxplots. Data normality was checked using histograms and the Shapiro–Wilk test. Normally distributed data sets were compared using parametric hypothesis tests (t test, paired t test, one-way ANOVA, two-way ANOVA, one-way repeated measure ANOVA). Non-normally distrusted data sets were compared using nonparametric tests (Wilcoxon, Kruskal–Wallis, and Friedman tests). Results provided by these parametric and nonparametric tests were also verified using plots (plot of means and boxplots).