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In addition to the standard deviation, a very common measure of variability is the variance. If you know the standard deviation of a set of scores, you can easily compute the variance of that same set of scores; the variance is simply the square of the standard deviation, as shown in the following formula:

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where

  • s2 is the variance,
  • Σ is the summation of deviations from the mean squared,
  • X is the data point,
  • X¯ is the mean of the set of data points,
  • n is the sample size.

Consider the data set of 10 observations as follows:

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which has a mean of 6. From the above formula, the value of the variance is 4.00.

Excel's VAR Function

While variance is a relatively easy descriptive statistic to compute by hand, it is much easier to use a software package such as Excel and the VAR function.

To compute the variance of a set of numbers by means of Excel, follow these steps:

  • Enter the individual scores into one column in a worksheet. The data in this example were entered into cells A1 through A10.
  • Select the cell into which you want to enter the VAR function. In this example, we are going to compute the variance in cell A11.
  • Now click on cell A11 and type the Average function as follows,

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    and press the Enter key.

  • As you can see in Figure 1, the variance was computed and the value returned to cell A11. Notice that in the formula bar in Figure 1, you can see the VAR function fully expressed and the value computed.
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Figure 1 Using the VAR Function to Compute the Variance

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Figure 2 Using the Data Analysis ToolPak to Compute the Variance and Other Descriptive Statistics

Using the Excel Data Analysis ToolPak

The variance can also be computed easily with Excel's Data Analysis ToolPak, as shown in Figure 2. Here, the Data Analysis option was selected from the Tools menu, the Descriptive Statistics option was selected, and the range of data and location for output were identified. The results show a complete descriptive analysis of the data.

Neil J. Salkind

Further Reading

Salkind, N. J.(2004).Statistics for people who (think they) hate statistics (2nd ed.).Thousand Oaks, CA: Sage.
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