DA0-002 Data Analysis Practice Question
In an A/B test, the null hypothesis states that there is no difference between the control and treatment groups. After running the test, the p-value is 0.04. Assuming α = 0.05, what is the correct conclusion?
⚠ Common exam trap
The trap is misinterpreting the p-value as the probability that the null hypothesis is true, or thinking that a low p-value means the test is invalid; candidates might also incorrectly choose 'accept the null' instead of 'fail to reject'.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Reject the null hypothesis
The p-value of 0.04 is less than the significance level α = 0.05, so we reject the null hypothesis. This means there is statistically significant evidence to suggest a difference between the control and treatment groups. The correct conclusion is to reject the null hypothesis.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Fail to reject the null hypothesis
Why it's wrong here
Since 0.04 < 0.05, the result is statistically significant and the null hypothesis is rejected, not retained. It tempts because a small p-value is sometimes misread as weak evidence, but it actually indicates the observed difference is unlikely under the null.
- ✓
Reject the null hypothesis
Why this is correct
The p-value of 0.04 falls below the significance level of 0.05, so the observed difference is statistically significant. The null hypothesis of no difference between control and treatment is rejected, supporting the conclusion that the treatment had an effect.
- ✗
Accept the null hypothesis
Why it's wrong here
A p-value of 0.04 is below α = 0.05, so the null hypothesis is rejected; accepting it inverts the decision rule. It tempts because failing to reject is often loosely called accepting, but the null is never affirmatively accepted.
- ✗
The test is invalid because the p-value is too low
Why it's wrong here
A p-value of 0.04 is perfectly valid; low values indicate evidence against the null, not invalidity. It tempts because very small p-values can suggest an overpowered or flawed test, but 0.04 is unremarkable and the test stands.
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Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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