DA0-002 Data Analysis Practice Question
A data scientist is performing a hypothesis test with a significance level α=0.05. The p-value obtained is 0.03. What should the scientist conclude?
⚠ Common exam trap
DA0-002 often tests the misconception that a small p-value means 'accept the null' or that p-values should be compared to a value other than the stated α — candidates confuse rejection logic or misread the threshold.
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 because the p-value is less than the significance level.
The decision rule for hypothesis testing is: if p-value < α, reject the null hypothesis. Here p = 0.03 and α = 0.05, so 0.03 < 0.05, meaning the result is statistically significant and the null hypothesis should be rejected in favor of the alternative. This indicates the observed effect is unlikely to have occurred by chance alone at the 5% significance level.
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 because the p-value is less than the significance level.
Why this is correct
With α=0.05, a p-value of 0.03 falls inside the rejection region, so the null hypothesis is rejected. This satisfies the stem's stated significance level and p-value, indicating the observed result is statistically significant at that threshold.
- ✗
Fail to reject the null hypothesis because the p-value is greater than 0.01.
Why it's wrong here
The comparison is against the stated significance level α=0.05, not 0.01. Since 0.03 < 0.05, the null hypothesis is rejected. Failing to reject would require a p-value exceeding α. The 0.01 threshold is irrelevant here and misapplies the decision criterion.
- ✗
The test is inconclusive, need a larger sample size.
Why it's wrong here
A p-value of 0.03 against α=0.05 yields a definite decision: reject the null hypothesis. Declaring the test inconclusive misstates the outcome; sample size is a design consideration, not a conclusion drawn after computing p. No ambiguity exists at these values.
- ✗
Accept the null hypothesis because the p-value is small.
Why it's wrong here
A p-value of 0.03 falls below α=0.05, so the null hypothesis is rejected, not accepted. Accepting the null is never a valid outcome of a significance test; you either reject or fail to reject. This option inverts the decision rule entirely.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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