MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is exploring a dataset with a binary target variable. Which TWO metrics are appropriate for evaluating the balance of the target classes? (Choose two.)
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
✓
Count plot of the target variable
Options A and D are correct. A count plot directly visualizes the frequency of each class in the target variable, making it easy to assess balance. Similarly, value_counts() returns the exact count of each class, providing a numeric measure of balance. Option B (histogram) is designed for continuous variables; while it can depict the counts of two categories, it is not the standard or most appropriate method for evaluating binary class balance. Option C (scatter plot) is used to explore relationships between two numeric features and does not show class distribution. Option E (correlation matrix) measures linear relationships between numeric features and is irrelevant for assessing target class balance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Count plot of the target variable
Why this is correct
Count plot shows frequency of each class.
- ✗
Histogram of a feature
Why it's wrong here
Histogram shows distribution of a continuous variable, not class balance.
- ✗
Scatter plot of two features colored by target
Why it's wrong here
Scatter plot shows feature relationship, not class balance.
- ✓
value_counts() on the target column
Why this is correct
value_counts() returns counts of unique values.
- ✗
Correlation matrix of all features
Why it's wrong here
Correlation matrix shows relationships between features, not class frequencies.
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