Non-parametric hypotheses tests

1. Non-parametric hypotheses tests Marek Majdan Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

2. Introduction • Nonparametric tests used in cases when data distribution can not be considered normal • Used alternatively to parametric tests (t test, ANOVA, chi-square) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

3. Wilcoxon test and Mann Whitney test • Wilcoxon test used alternatively to paired t test • Mann whitney test used alternatively to two sample t test • In R: wilcox.test(y~A) - where y is numeric and A is A binary factor wilcox.test(y,x) - where y and x are numeric wilcox.test(y1,y2,paired=TRUE)- where y1 and y2 are numeri Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

4. Kruskall Wallis • Used alternatively to ANOVA test In R: kruskal.test(y~A)- where y1 is numeric and A is a factor Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

5. Post Hoc test for Kruskall Wallis test • Compares groups between each other • In R: kruskalmc (y ~ A, data=database) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

6. Fishers exact test for proportions • Used alternatively to chi-square test when counts are less than 5 • Originally for 2x2 tables only but in R it is implemented for larger tables • In R: fisher.test (x) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com