So I have the following tables (simplified here):
this is Ost_data
Raumeinheit | Langzeitarbeitslose |
---|---|
Hamburg | 22 |
Koln | 45 |
This is West_data
Raumeinheit | Langzeitarbeitslose |
---|---|
Hamburg | 42 |
Koln | 11 |
Ost_data has 76 rows and West_data has 324 rows.
I am tasked with proving my hypothesis that the Variable "Langzeitarbeitslose" is statistically, significantly higher in Ost_data than in West_data. Because that variable is not normally distributed I am trying to use Pearson's Chi Square Test.
I tried
chisq.test(Ost_data$Langzeitarbeitslose, West_data$Langzeitarbeitslose)
but that just retuns that it can't be performed because x and y differs in length.
Is there a way to navigate around that problem and perform the Chi Square test regardless with my two tables which have varying lengths?
CodePudding user response:
Pearson's ChiSq test is when the rows are measuring the same thing. It sounds like here your rows are just measuring some quantity on repeated samples, so you should use a t-test.
t.test(Ost_data$Langzeitarbeitslose, West_data$Langzeitarbeitslose)