DA0-002 Data Analysis Practice Question
An analyst wants to compare the mean sales revenue across three different store regions. The data is normally distributed and variances are equal. Which statistical test is most appropriate?
⚠ Common exam trap
The trap is reaching for a t-test when comparing more than two groups — candidates must recognize that three or more independent group means require ANOVA, not repeated t-tests.
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
✓
ANOVA
ANOVA (Analysis of Variance) is the correct test for comparing means across three or more groups when data is normally distributed and variances are equal (homogeneity of variance). It tests the null hypothesis that all group means are equal using an F-statistic comparing between-group to within-group variance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Two-sample t-test
Why it's wrong here
A two-sample t-test compares means between exactly two groups, so it cannot simultaneously assess three store regions. It is tempting because it correctly handles normally distributed data with equal variances, and would be the right choice when comparing, say, two regions only. Extending it to three groups requires multiple pairwise tests, inflating Type I error.
- ✓
ANOVA
Why this is correct
ANOVA compares means across three or more independent groups in a single test, keeping the Type I error rate controlled. With normal distributions and equal variances, the parametric F-test assumptions hold, making it appropriate for the three store regions.
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Paired t-test
Why it's wrong here
A paired t-test requires matched observations from the same subjects measured twice, such as before-and-after readings on identical units. Here the three regions contain independent groups, so no pairing exists and the test cannot compare three means. It would be correct for comparing two measurements taken on the same stores.
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Chi-square test
Why it's wrong here
The chi-square test assesses association between categorical variables or goodness-of-fit against expected frequencies, so it cannot compare means of a continuous variable across groups. It is tempting because it also handles three or more groups, and would be correct for testing whether region and sales category are independent.
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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
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.