MLS-C01 Exploratory Data Analysis Practice Question
Which TWO are appropriate techniques for detecting outliers in a dataset during exploratory data analysis?
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
✓
Z-score method (assuming normal 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.
- ✓
Z-score method (assuming normal distribution)
Why this is correct
Z-score identifies outliers based on standard deviations.
- ✗
One-hot encoding
Why it's wrong here
One-hot encoding is for categorical features.
- ✗
Principal component analysis (PCA)
Why it's wrong here
PCA is for dimensionality reduction.
- ✗
t-SNE
Why it's wrong here
t-SNE is for visualization.
- ✓
Interquartile range (IQR) method
Why this is correct
IQR method uses quartiles to detect outliers.
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