medium · FRM Part 1 Quantitative Analysis
A researcher is using a bootstrap to estimate the p-value for a hypothesis test. They find that the bootstrap p-value is 0.06, while the parametric p-value (based on a t-test) is 0.04.
What is the most likely conclusion?
- The bootstrap p-value is incorrect because it is always lower than the parametric p-value.
- The bootstrap is less 'powerful' than the t-test, meaning it is more likely to commit a Type II error.
- The parametric test was likely overstating the significance because the underlying data has fatter tails than a t-distribution assumes.
- The analyst should reject the null hypothesis because at least one of the tests showed a p-value below 0.05.
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