Teaching statistics and chemometrics using an open source, free and graphical user interface software.

This report aims to introduce the fundamental features of the JAMOVI software to academics in the chemistry field for use in undergraduate and graduate-level research. It is freeware with a graphical user interface (GUI) and it is written in the R language. The discussion began on descriptive statistics ( mean, median, range, skewness how to check data normality using hypothesis tests (Shapiro-Wilk, Kolmogorov-Smirnov and Anderson-Darling tests). Then, some visual tools for checking data normality were presented (histograms, Q-Q plots, and boxplots). When the data normality was checked, two and more dependent means were compared using parametric tests (t test and ANOVA; Fisher’s). When the data was not normally distributed, nonparametric tests were used (Mann-Whitney and Kruskal-Wallis tests). When the data was paired and normally distributed, two and more than two group means were compared using the paired t-test and RMANOVA, respectively. Their nonparametric versions were also used (Wilcoxon and Friedman tests). Means comparisons were also carried out using boxplots and discriminant plots, which provide a visual interpretation beyond the p-values interpretation. In addition, principal component analysis (PCA) was carried out using JAMOVI's plugin MEDA, which builds scores and loading plots. All tests and plots were done easily using JAMOVI's click-and-go interface.