MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is analyzing a dataset with a binary target variable. They compute the correlation matrix and find that all features have correlations between -0.1 and 0.1 with the target. They suspect that the relationship might be non-linear. Which of the following techniques should they use to detect non-linear relationships?
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
✓
Mutual information
Mutual information is the correct technique because it measures the dependency between variables and can capture any type of relationship, including non-linear and non-monotonic. Options A and C are incorrect: ANOVA is used for comparing means of categorical vs continuous variables, and Pearson correlation only measures linear relationships. Option B is also incorrect: Spearman's rank correlation captures monotonic relationships but may miss other non-linear patterns.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
ANOVA test
Why it's wrong here
Tests differences in means across groups, not general association.
- ✗
Spearman's rank correlation
Why it's wrong here
Captures monotonic relationships, not all non-linear.
- ✗
Pearson correlation coefficient
Why it's wrong here
Only captures linear relationships.
- ✓
Mutual information
Why this is correct
Measures any kind of dependency, linear or non-linear.
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