Standard deviation measures:

**The reasoning** Standard deviation tells you **how spread out** your data is from the average (mean). That's what "dispersion" means—the scatter or variability in your dataset. Imagine two classes both scored an average of 60% in a test. In Class A, most students got between 55-65%. In Class B, scores ranged from 20-95%. Both have the same mean, but Class B has much **higher dispersion**—the scores are scattered far from the average. Standard deviation would be small for Class A and large for Class B. The formula √[Σ(x - x̄)²/n] literally measures how far each value (x) deviates from the mean (x̄), then averages those deviations. It's a **dispersion measure**, pure and simple. **Why the wrong options tempt you** - **A (Mean)**: You might confuse this because standard deviation *uses* the mean in its calculation, but it doesn't measure the mean itself. - **C (Skew only)**: Skewness is different—it measures asymmetry, not spread. - **D (Mode)**: Mode is the most frequent value; totally unrelated. **Quick takeaway** Standard deviation = how scattered your data is around the average—always remember: **dispersion = spread**.