What does a significant result in a Chi-square test imply?
For a Chi-square test, a p-value that is less than or equal to your significance level indicates there is sufficient evidence to conclude that the observed distribution is not the same as the expected distribution. You can conclude that a relationship exists between the categorical variables.
What is the limitation of chi-square test?
Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer’s V to produce relative low correlation measures, even for highly significant results.
How is the chi square test applied to two independent comparison groups?
Here we extend that application of the chi-square test to the case with two or more independent comparison groups. Specifically, the outcome of interest is discrete with two or more responses and the responses can be ordered or unordered (i.e., the outcome can be dichotomous, ordinal or categorical).
Is the chi square statistic based on ranks?
The comparisons are based on ranks, and the test statistic is distributed as a chi-square. hope this helps. Yes, I was not precise. I was running K-W test (I just wrote about chi-square because it is based on such distribution).
Where to find critical value in chi squared test?
We find the critical value in a table of probabilities for the chi-square distribution with degrees of freedom (df) = k-1. In the test statistic, O = observed frequency and E=expected frequency in each of the response categories.
Is there a method to check which groups differ significantly?
After running Chi-square test for comparison between 3 groups, is there a method of checking which groups differ significantly? I have to compare prosocialness level (measured at ordinal scale) between 3 experimental conditions. I decided to run chi-square test (was it a good decision?).