 # What Is a Standard Deviation?

By Charles Joseph | Editor, Financial Affairs
Reviewed by Corey Michael | Senior Financial Analyst

A standard deviation is a statistic that measures the dispersion of a dataset relative to its mean. The standard deviation is calculated as the square root of variance by determining each data point’s deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.

## Related Questions

1. What is Variance in statistics?

Variance is a statistical measurement that depicts the spread between numbers in a data set. It shows how far each number in the set is from the mean (average) and, thus, from every other number in the set. It’s often denoted by the symbol σ².

2. What does a high Standard Deviation mean?

## Want More Financial Tips?

We respect your privacy and you can unsubscribe anytime.

A high standard deviation suggests a greater variability in data points. In other words, data points are spread out over a wider range. If the data is generally clustered closely to the average, the standard deviation is low. If the data is dispersed over a larger range of values, the standard deviation is high.

3. How is Standard Deviation used in finance?

In the world of finance, standard deviation serves as a gauge for investment risk. A volatile stock has a high standard deviation, indicating that its price fluctuates significantly. This renders it riskier than a stock with lower standard deviation.

4. Can Standard Deviation be negative?

No, standard deviation cannot be negative. Since it’s calculated as the square root of variance, and squares are always positive or zero, standard deviation is always non-negative.

5. How does Standard Deviation affect data analysis?

Standard deviation significantly influences data analysis as it allows analysts to understand whether the data points are generally close to the mean or widely dispersed. This insight is crucial in fields like finance, physics, and environmental science to predict future trends, test theories, or draw conclusions.