Answer: Fail to reject the null hypothesis.

## Explanation In statistical hypothesis testing: - **P-value (1.4%)**: The probability of observing a result as extreme as, or more extreme than, the observed result if the null hypothesis were true - **Significance level (1%)**: The threshold set by the researcher for rejecting the null hypothesis ### Decision Rule: - If p-value ≤ significance level → **Reject** null hypothesis - If p-value > significance level → **Fail to reject** null hypothesis Since 1.4% > 1%, the candidate would **fail to reject** the null hypothesis. ### Why Other Options Are Incorrect: **A. Reject the null hypothesis** - Incorrect because p-value (1.4%) > significance level (1%) **C. Conclude that the mean return is different from zero** - Incorrect because failing to reject the null hypothesis means we don't have sufficient evidence to conclude the mean is different from zero **D. Conclude that the mean return is negative** - Incorrect because the test only determines if the mean is different from zero, not the direction of the difference ### Key Takeaway: A p-value greater than the significance level indicates insufficient evidence to reject the null hypothesis, meaning we cannot conclude the mean return is statistically different from zero.

Author: Tanishq Prabhu