CompTIA Data+ (DA0-002)Data AnalysisMedium
A data analyst is performing a hypothesis test to determine if a new website design leads to a statistically significant increase in conversion rates. They have set up their null and alternative hypotheses. After collecting data and running the statistical test, they obtain a p-value of 0.03. If the chosen significance level (alpha) for this test is 0.05, what conclusion should the analyst draw?
- AFail to reject the null hypothesis, as the p-value is greater than alpha.
- BReject the alternative hypothesis, as the p-value is less than alpha.
- CFail to reject the null hypothesis, as the p-value is less than alpha.
- DReject the null hypothesis, as the p-value is less than alpha.
Show answer & explanationAnswer & explanation
Correct answer: D. Reject the null hypothesis, as the p-value is less than alpha.
In hypothesis testing, if the p-value (0.03) is less than the chosen significance level (alpha = 0.05), it indicates that the observed data is unlikely to have occurred under the null hypothesis. Therefore, the null hypothesis should be rejected in favor of the alternative hypothesis.
Why the other options are wrong
- A. This is incorrect; the p-value is less than alpha, not greater.
- B. We either reject or fail to reject the null hypothesis, not the alternative hypothesis directly.
- C. This is incorrect; a p-value less than alpha leads to rejecting the null.
P-value and Significance Level
The p-value is the probability of observing data as extreme as, or more extreme than, the observed data, assuming the null hypothesis is true. The significance level (alpha) is the threshold below which the null hypothesis is rejected.
- If p-value < alpha, reject the null hypothesis.
- If p-value ≥ alpha, fail to reject the null hypothesis.
- Alpha is typically set at 0.01, 0.05, or 0.10.
Memory trick: P-value low, null must go! P-value high, null can fly!