A data scientist observes findings that indicate that as electrical grids in a country become...

→ Kurtosis is a statistical measure that describes the "tailedness" or extremity of values in a distribution. The observation that smaller events decrease while extreme events increase indicates a rise in heavy tails — a textbook sign of increasing kurtosis. This reflects a distribution becoming more prone to extreme values (e.g., more impactful blackouts).

Why the other options are incorrect:

A: “Scale axis magnitudes” is not a statistical metric but refers to plotting.

C: Skewness measures asymmetry, not the frequency of extreme values.

D: Normality checks whether a distribution follows the normal distribution, not its tail behavior.

Official References:

CompTIA DataX (DY0-001) Official Study Guide – Section 1.3:“Kurtosis measures the presence of outliers and extreme values in a distribution — higher kurtosis suggests more frequent extreme events.”

Applied Statistical Analysis, Chapter 4:“Kurtosis provides insight into the likelihood of extreme deviations and is useful in risk and reliability analysis.”

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