The concept of variance partially resembles the mean absolute deviation. However, instead of taking absolute values, we elevate it to the second degree.
Population variance denoted by sigma squared is equal to the sum of squared differences between the observed values and the population mean, divided by the total number of observations. Standard deviation is given by the square root of variance. Closer the number to the mean, the lower the obtained result; and the further the number lies from the mean, the larger the difference. This gives us an idea about a dataset’s variability.
Calculating standard deviation provides information about the average volatility we can expect in a positive or a negative direction from the mean.
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Variance and Standard Deviation are among the topics included in the Quantitative Methods module of the CFA Level 1 Curriculum.