Standard deviation describes the dispersion of data points around the mean (average) value; a larger standard deviation indicates that more of the data points are distant from the mean in either direction, i.e., the data are more spread out. For normally distributed data, approximately 68% of the data points lie within 1 standard deviation of the mean, approximately 95% lie within 2 standard deviations, and approximately 99% lie within 3 standard deviations.

To help visualize this concept, Figure 1 shows how fasting plasma glucose concentrations in US adults would be spread around the average fasting plasma glucose if they followed a normal distribution. The mean (average) fasting plasma glucose in US adults is 104 milligrams per deciliter (mg/dl).^[1] The pink shaded area represents the people in whom fasting plasma glucose is between 2 standard deviations above and 2 standard deviations below the mean (average) fasting plasma glucose. In other words, the pink shaded area represents 95% of the population. (Please note that fasting plasma glucose concentrations are usually not normally distributed in many populations; here, we’re just assuming they have a normal distribution for illustrative purposes.)