MLS-C01 Exploratory Data Analysis Practice Question
A machine learning engineer notices that the target variable in a regression dataset has a long-tailed distribution. Which visualization technique is most appropriate to assess the distribution before applying a log transformation?
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
✓
Histogram with density curve
(Histogram with density curve) is the most appropriate visualization for assessing a long-tailed distribution because it clearly shows the shape, spread, and tail behavior of the target variable. A histogram with an overlaid density curve helps identify skewness and the need for a log transformation. Option A (Bar chart) is for categorical data, not continuous distributions. Option C (Box plot) provides quartiles and outliers but does not fully reveal the distribution shape, especially the length of tails. Option D (Scatter plot) visualizes relationships between two variables, not a univariate distribution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Bar chart
Why it's wrong here
Bar charts are for categorical data.
- ✓
Histogram with density curve
Why this is correct
Histogram and density curve show the distribution shape, including long tails.
- ✗
Box plot
Why it's wrong here
Box plot shows summary statistics but not the detailed distribution shape.
- ✗
Scatter plot
Why it's wrong here
Scatter plots are for bivariate relationships.
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