DA0-002 Data Analysis Practice Question
A data analyst is working with a dataset that includes a column 'income' with values ranging from 20,000 to 150,000. To standardize this variable for a linear regression that assumes normally distributed residuals, which method should be used?
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 standardization
Z-score standardization transforms data to have mean 0 and standard deviation 1, which is suitable for algorithms that assume normality (like linear regression).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Log transformation
Why it's wrong here
Log transformation is for reducing skewness, not for standardizing to normal distribution.
- ✗
Min-max normalization
Why it's wrong here
Min-max normalization does not produce a standard normal distribution.
- ✗
Square root transformation
Why it's wrong here
Similar to log, not standardization.
- ✓
Z-score standardization
Why this is correct
Correct: Z-score centers and scales to unit variance, suitable for normality assumptions.
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