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).