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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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