What are the limitations of the chi-square test?

What are the limitations of the chi-square test?

The chi-square test has several limitations, including its sensitivity to sample size, the requirement for expected frequencies, and its inability to determine causation.

Can you explain why sample size affects the chi-square test?

Certainly! A larger sample size can lead to significant results even for small differences, while a small sample may not provide reliable results.

What do you mean by expected frequencies?

Expected frequencies are the theoretical frequencies we expect in each category if the null hypothesis is true. The chi-square test requires these to be sufficiently large.

Are there alternatives to the chi-square test?

Yes, alternatives include Fisher's Exact Test for small sample sizes and logistic regression for more complex relationships.

How can I improve my analysis if I encounter these limitations?

You can consider using larger sample sizes, ensuring adequate expected frequencies, or applying different statistical tests that suit your data better.