DA0-002 Data Analysis Practice Question
During data exploration, an analyst notices that the target variable has a heavily right-skewed distribution. Which data transformation would be most appropriate to make the distribution more symmetric?
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
✓
Log transformation
Log transformation is appropriate for heavily right-skewed distributions because it compresses the high values and spreads out the low values, making the distribution more symmetric. Square root transformation is better for moderate skew, and reciprocal transformation is for severe skew. Therefore, option A (Log transformation) is correct.
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 this is correct
Log transformation effectively reduces right skewness.
- ✗
Reciprocal transformation
Why it's wrong here
Reciprocal reverses order and may not help.
- ✗
No transformation needed
Why it's wrong here
Transformations are needed for many algorithms to perform well.
- ✗
Square root transformation
Why it's wrong here
Square root is for moderate skew, but log is stronger for heavy skew.
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