What is a key advantage of standard deviation compared to variance?

Standard deviation is favored for its intuitive interpretation regarding the spread of data because it is expressed in the same units as the original data. This characteristic allows for a clearer understanding of the data's variability. When you calculate standard deviation, you take the square root of the variance, which means that any unit of measurement for the data (e.g., meters, dollars, or kilograms) is preserved. Thus, if the data is measured in dollars, the standard deviation will also be in dollars, making it directly applicable and easier to comprehend in the context of the data set.

In contrast, variance is the average of the squared deviations from the mean, which results in a metric that is in squared units (for instance, dollars squared). This can make interpreting variance more complex, as it does not provide a readily understandable measure of dispersion in relation to the original data scale.

By understanding that standard deviation retains the units of the original data, one can more readily communicate and apply the findings of data analysis to real-world situations, enhancing insights derived from the data.