Kruskal Wallace Test on Column

Hi,

I have three seperate tables.

There is one column in each table I want to compare - temperature

The data are not normally distributed.

So, I can use a Kruskal Wallace test to compare the means of the three columns

My problem: the test seems to work on 1 array only (x) - but I have three

p = kruskalwallis(x)

How should I write the code to conduct the test?

I tried concatenating the tables but they each have a different number of rows - so it is not working.

Advice welcome.

Answer 1

[Adam Danz]

The p = kruskalwallis(x) test works on columns of x. If all of your tables have the same number of rows, you just have to extract the values from each table into a matrix. If the tables only have 1 variable, as you described, it's as easy as,

T1 = table(rand(20,1)); 
T2 = table(rand(20,1)+1);
T3 = table(rand(20,1)+.5);

p = kruskalwallis([T1{:,:},T2{:,:},T3{:,:}])
% or
p = kruskalwallis([T1.Var1,T2.Var1,T3.Var1])

If the tables do not have equal rows, you must concatenate them into a single column and use a grouping variable p = kruskalwallis(x,group)

x = [T1.Va1;T2.Var1;T3.Var1]; 
group = [1 + zeros(size(T1.Var1)); 2 + zeros(size(T2.Var1)); 3 + zeros(size(T3.Var1))];
p = kruskalwallis(x,group)

[Sarah Yun]

Hi Adam,

Unfortunately, my 3 tables do not have equal rows. So, I must use a grouping variable. Please can you help me with this? Thank you. Sarah.

[Adam Danz]

Yep! I just added an example at the bottom of my answer. If you get stuck, show me the code you're using and describe the problem and I'd be happy to help straighten things out.