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

Step 1: Understanding the Question:
We need to compare two proportions (40% versus 60%) obtained from two different, independent samples, and choose the correct statistical test for this comparison.

Step 2: Key Concept:
When comparing proportions (categorical, qualitative data) between two independent groups, and the sample size in each group is reasonably large, the chi square test is the standard choice. It checks whether the observed difference in proportions could have arisen by chance.

Step 3: Detailed Explanation:
The Fischer exact test is used instead of chi square only when sample sizes are very small, typically when any expected cell count in the contingency table falls below 5. The question does not indicate such a small sample, so chi square is preferred.
Paired t test compares the means of two related, quantitative measurements taken on the same subjects, such as before and after readings. Here we have two separate independent samples and a proportion, not a paired quantitative variable, so this test does not apply.
ANOVA test is used to compare means across three or more independent groups for a quantitative variable. Here there are only two groups and the outcome is a proportion, not a continuous mean, so ANOVA is not suitable.

Step 4: Final Answer:
Since we are comparing two proportions from independent samples with an adequate sample size, the chi square test is the best choice.
\[ \boxed{\text{Chi square test}} \]