Non-Parametric Version of OneWay ANOVA

Non-parametric One way ANOVA

1) If the condition of normality of residuals is not met,

we implement the kruskal wallis test

kruskal.test(weight ~ group, data= PlantGrowth)

## 
##  Kruskal-Wallis rank sum test
## 
## data:  weight by group
## Kruskal-Wallis chi-squared = 7.9882, df = 2, p-value = 0.01842

pairwise.wilcox.test(PlantGrowth$weight, PlantGrowth$group,
                     p.adjust.method = "BH")

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot
## compute exact p-value with ties

## 
##  Pairwise comparisons using Wilcoxon rank sum test 
## 
## data:  PlantGrowth$weight and PlantGrowth$group 
## 
##      ctrl  trt1 
## trt1 0.199 -    
## trt2 0.095 0.027
## 
## P value adjustment method: BH

2) where the homogeneity of variance assumption is violated

oneway.test(weight ~ group, data= PlantGrowth)

## 
##  One-way analysis of means (not assuming equal variances)
## 
## data:  weight and group
## F = 5.181, num df = 2.000, denom df = 17.128, p-value = 0.01739