MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is performing EDA on a dataset with a binary target variable. Which THREE techniques can help assess the relationship between a continuous feature and the target?
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
✓
KDE plot grouped by target
Box plots (comparing distributions for each class), histograms (overlay or side-by-side), and KDE plots (probability density) are all effective for visualizing the relationship between a continuous feature and a binary target. Option A (scatter plot) requires two continuous variables. Option D (bar chart) is for categorical features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Scatter plot against another continuous feature
Why it's wrong here
Scatter plots show relationship between two continuous variables, not directly with target.
- ✓
KDE plot grouped by target
Why this is correct
KDE plots show smoothed density per class.
- ✓
Histogram colored by target
Why this is correct
Histograms can compare distributions per class.
- ✗
Bar chart of feature values
Why it's wrong here
Bar charts are for categorical features.
- ✓
Box plot grouped by target
Why this is correct
Box plots show distribution differences between classes.
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Same concept, more angles
1 more way this is tested on MLS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data scientist is performing EDA on a dataset with both numeric and categorical features. Which TWO techniques are appropriate for visualizing the relationship between a numeric feature and a binary categorical target?
medium- A.Histogram
- B.Stacked bar chart
- ✓ C.Violin plot grouped by target
- ✓ D.Box plot grouped by target
- E.Scatter plot
Why C: Correct options are C (violin plot grouped by target) and D (box plot grouped by target). Both are effective for visualizing the distribution of a numeric feature across two categories of a binary target. A violin plot combines a box plot and a density plot, showing the full distribution shape, while a box plot displays medians, quartiles, and outliers. Option A (histogram) shows distribution of a single numeric variable but does not directly compare groups. Option B (stacked bar chart) is for categorical vs categorical data. Option E (scatter plot) is for two numeric variables.
JA
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