Question 32
Domain 2: Data ProcessingA data analyst is reviewing a variable whose values span several orders of magnitude and are heavily right-skewed. In this situation, when is a log scale transformation most appropriate?
Correct answer: B
Explanation
A log scale transformation is most appropriate when data span a very wide range of values, especially across multiple orders of magnitude. It is commonly used to make highly skewed data easier to analyze and interpret. — official.txt
Why each option is right or wrong
A. When the variable is already evenly distributed across a narrow range of values
Log scaling is used for wide-ranging or highly skewed values, not narrow evenly distributed data.
B. When the variable covers several orders of magnitude and shows strong right skew
The source material identifies log scale transformation as appropriate for scenarios involving data that span very different magnitudes. In this question, the values cover several orders of magnitude and are heavily right-skewed, matching the situation where a log scale transformation should be used.
C. When the variable contains only a small number of repeated categorical labels
Log scale transformation applies to numeric magnitude patterns, not categorical labels.
D. When the variable must remain in its original scale to preserve direct visual spacing
Log transformation changes the scale and is chosen when the original scale is less useful for wide-ranging data.