Question

In a particular trial, the association of lung cancer with smoking is found to be 40% in one sample and 60% in another. What is the best test to compare the results?

• A. Chi square test
• B. Fischer test
• C. Paired t test
• D. ANOVA test

Hint:

Comparing two proportions from independent samples calls for the chi square test.

Answer 1

The Correct Option is A

This question is about picking the right statistical test to compare two proportions collected from two separate samples.

1. Chi square test: Used to compare proportions (categorical data) between independent groups when sample sizes are adequate. This fits comparing 40 percent versus 60 percent from two samples.
2. Fischer test: Used in place of chi square only when the sample is very small and expected cell counts fall below 5. No such small sample is described here.
3. Paired t test: Used for comparing two related, quantitative measurements on the same subjects, such as pre and post readings, not for independent proportions.
4. ANOVA test: Used to compare means of a quantitative variable across three or more groups, which does not match a two group proportion comparison.

Because the data here are proportions from two independent samples with adequate size, the chi square test is the correct method to check if the difference is statistically significant.

Let's summarize:

• Chi square compares proportions between independent groups.
• Fischer test is reserved for very small samples, and paired t test and ANOVA are for quantitative, not categorical, comparisons.

So the best test to compare these two results is the chi square test.