In gaming analytics, which statement correctly distinguishes variance from volatility?

In gaming analytics, which statement correctly distinguishes variance from volatility?

• A. Variance describes the distribution of outcomes around expected value.
• B. Variance is the same as volatility.
• C. Volatility measures the average profit per game.
• D. Volatility describes the risk profile (frequency and size of wins/losses).

Answer: (A)

The key idea being tested is the difference between a static dispersion measure and a time-based fluctuation measure. Variance describes how spread out the outcomes are around the expected value; it’s a single-number summary of how much results can deviate from what you’d expect, calculated from the distribution itself. Volatility, in contrast, is about how those results move over time—the speed and size of swings in a time series, which matters for risk and capital planning. That’s why the statement that variance describes the distribution of outcomes around the expected value is the best choice. It directly defines what variance measures. The other ideas mix in time-based behavior or mean-level concepts (average profit) and don’t isolate variance’s role as dispersion around the mean.

The key idea being tested is the difference between a static dispersion measure and a time-based fluctuation measure. Variance describes how spread out the outcomes are around the expected value; it’s a single-number summary of how much results can deviate from what you’d expect, calculated from the distribution itself. Volatility, in contrast, is about how those results move over time—the speed and size of swings in a time series, which matters for risk and capital planning.

That’s why the statement that variance describes the distribution of outcomes around the expected value is the best choice. It directly defines what variance measures. The other ideas mix in time-based behavior or mean-level concepts (average profit) and don’t isolate variance’s role as dispersion around the mean.