MLS-C01 Exploratory Data Analysis Practice Question
A data scientist wants to understand the statistical relationship between two categorical variables in a dataset. Which test is most appropriate?
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-squared test
The chi-squared test is used to determine if there is a significant association between two categorical variables, which is exactly what the data scientist wants to understand. Option B (Pearson correlation coefficient) is incorrect because it measures linear relationship between two continuous variables. Option C (Student's t-test) is used to compare means of two groups, typically for continuous data. Option D (ANOVA) is used to compare means across three or more groups, also for continuous data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Chi-squared test
Why this is correct
Correct: Chi-squared test is used for association between categorical variables.
- ✗
Pearson correlation coefficient
Why it's wrong here
Incorrect: Pearson correlation requires continuous variables.
- ✗
Student's t-test
Why it's wrong here
Incorrect: t-test compares means of two groups.
- ✗
ANOVA test
Why it's wrong here
Incorrect: ANOVA compares means of a continuous variable across categories.
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