DA0-002 Data Analysis Practice Question
A data analyst is performing a hypothesis test with a significance level of 0.05. The p-value obtained is 0.03. What should the analyst conclude?
⚠ Common exam trap
Candidates often confuse 'fail to reject' with 'accept' the null hypothesis, or they mistakenly think a p-value less than α means the null hypothesis is proven false with certainty, rather than just providing sufficient evidence to reject it.
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
Since the p-value (0.03) is less than the significance level (0.05), the result is statistically significant. This means the observed data provides sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis. The analyst should conclude that there is a statistically significant effect or difference.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Reject the null hypothesis
Why this is correct
The p-value of 0.03 falls below the 0.05 significance level, meaning the observed result is unlikely under the null hypothesis. The analyst therefore rejects the null hypothesis in favour of the alternative, accepting the result as statistically significant.
- ✗
Fail to reject the null hypothesis
Why it's wrong here
A p-value of 0.03 falls below the 0.05 significance level, so the null hypothesis is rejected, not retained. Failing to reject applies only when the p-value exceeds the threshold, for example 0.08. The option inverts the decision rule that compares the obtained p-value against the pre-set alpha.
- ✗
Accept the null hypothesis
Why it's wrong here
With a p-value of 0.03 below the 0.05 significance level, the null hypothesis is rejected, not accepted. Accepting it is tempting because failing to reject sounds like accepting, but the correct conclusion is that sufficient evidence exists to reject the null hypothesis in favour of the alternative.
- ✗
The result is practically significant
Why it's wrong here
Statistical significance does not imply practical significance.
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