Please permit that I first reproduce some data in the same format as yours:
fungi_vector <- data.frame( tmp_vector = c(rnorm(10, 0.7, 0.1), rnorm(10, 0.2, 0.1)), labels = c(rep('Ascomycota', 10), rep('Basidiomycota', 10))) fungi_vector$tmp_vector <- as.character(fungi_vector$tmp_vector) str(fungi_vector) 'data.frame': 20 obs. of 2 variables: $ tmp_vector: chr "0.651365595291301" "0.661684503596836" "0.755288193037626" "0.666716503201382" ... $ labels : chr "Ascomycota" "Ascomycota" "Ascomycota" "Ascomycota" ...
Então / So, the first issue is that your column of numbers is encoded as characters; so, we first need to convert that to numerical values:
fungi_vector$tmp_vector <- as.numeric(fungi_vector$tmp_vector)
To be proper, we should also convert the second column to categorical values:
fungi_vector$labels <- factor(fungi_vector$labels, levels = c('Ascomycota','Basidiomycota'))
Then, a Kruskal Wallis test can be done like this:
kruskal.test(tmp_vector ~ labels, fungi_vector) Kruskal-Wallis rank sum test data: tmp_vector by labels Kruskal-Wallis chi-squared = 14.286, df = 1, p-value = 0.0001571
For my 'manufactured' data, I already knew that the p-value would be statistically significant due to the fact that I had pre-selected different means via
rnorm() (see above).
We can also plot this:
boxplot(tmp_vector ~ labels, fungi_vector)
I will leave the remainder to you.