DA0-002 Chi-square test of independence Practice Question
A retail company wants to test whether a new website layout increases the conversion rate compared to the current layout. They randomly assign visitors to either the control or treatment group. Which statistical test is most appropriate to compare the conversion rates?
⚠ Common exam trap
DA0-002 often tests the distinction between tests for means (t-test, ANOVA) and tests for proportions/frequencies (chi-square) — candidates pick t-test because they see 'two groups' and forget the outcome is binary, not continuous.
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
✓
Chi-square test
The outcome variable is conversion (yes/no), a categorical binary variable, and the predictor is group (control vs treatment), also categorical. The chi-square test of independence is designed to compare observed versus expected frequencies across categories, making it the correct choice for comparing two conversion rates.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Two-sample t-test
Why it's wrong here
A two-sample t-test compares mean values of a continuous variable between two groups, but conversion rate is a proportion of successes and failures, violating its normality and variance assumptions. It would be correct for comparing continuous metrics such as average order value between the control and treatment groups.
- ✓
Chi-square test
Why this is correct
Conversion rate is a binary outcome (converted or not) across two independent groups, so the chi-square test compares observed versus expected frequencies in a contingency table. It satisfies the stem's requirement to test whether the new layout's conversion rate differs from the control.
- ✗
ANOVA
Why it's wrong here
ANOVA compares means across three or more groups defined by a categorical factor; here there are only two independent groups and a binary outcome, so its F-test targets the wrong structure. It would be correct for testing conversion differences across several layouts simultaneously, not a single control-versus-treatment comparison.
- ✗
Logistic regression
Why it's wrong here
Logistic regression models the probability of a binary outcome from predictor variables, so it estimates effect size rather than directly testing whether two independent proportions differ. It would be correct for adjusting conversion for covariates such as device type or traffic source, which this scenario does not require.
About these practice questions
Courseiva writes every DA0-002 question from scratch — 1,004 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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.