DA0-002 Data Analysis Practice Question
A data analyst at a logistics company is analyzing delivery times for three different shipping carriers. The analyst wants to determine whether the mean delivery time differs across carriers. The data are normally distributed, and the variances across carriers are assumed equal. Which statistical test should the analyst use?
⚠ Common exam trap
The trap here is assuming that an independent two-sample t-test can be extended to three groups without adjusting for multiple comparisons, which increases the risk of a false positive.
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
✓
One-way ANOVA
One-way ANOVA is designed to compare means across three or more independent groups under assumptions of normality and equal variances. The scenario involves three carriers, continuous delivery times, and the goal of detecting mean differences, making ANOVA the correct choice. Other tests either handle only two groups or require categorical data, which does not fit the analysis objective.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Independent two-sample t-test
Why it's wrong here
An independent two-sample t-test compares means between exactly two groups. Since there are three carriers, using this test would require multiple pairwise comparisons, which inflates the Type I error rate. A one-way ANOVA is designed to handle three or more groups simultaneously while controlling the overall error rate.
- ✓
One-way ANOVA
Why this is correct
One-way ANOVA compares the means of three or more independent groups to determine if at least one group mean is significantly different. Here, the analyst has three carriers, normal data, and equal variances, which satisfies the assumptions for ANOVA. It is the appropriate test to assess whether mean delivery times differ across the carriers.
- ✗
Paired t-test
Why it's wrong here
A paired t-test is used when comparing two related groups, such as before-and-after measurements on the same subjects. In this scenario, the carriers are independent groups, not paired, so a paired t-test is inappropriate. It would incorrectly treat the carriers as dependent samples, leading to invalid conclusions about differences in mean delivery times.
- ✗
Chi-square test of independence
Why it's wrong here
The chi-square test of independence examines relationships between two categorical variables. Delivery time is a continuous variable, and the goal is to compare means across carriers, not to test association between categories. Using chi-square would require binning the continuous data, losing information and not directly addressing the mean comparison.
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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.