Statistics How To

Variance in Minitab: How to Find it

Variance > Variance in Minitab

Watch the video to find a sample variance in Minitab or follow the steps below:

How to find the Variance in Minitab: Steps

variance in minitab

The sample variance formula.

Variance is a measure of variability in statistics. In other words, it gives you an idea of how far a data set is spread out. Variance can range from 0 to infinitely large. A variance of zero means that the numbers in a set are all the same. The larger the variance, the more spread out the data set. You can calculate the variance by finding the mean, subtracting the mean from each number in the set, squaring the result and then averaging the squared difference — or, you can let Minitab take care of the hard work for you!

Example question: Find the variance for the following sample: 12, 13, 24, 24, 25, 26, 34, 35, 38, 45, 46, 52, 53, 78, 78, 89

Step 1: Type your data into a column in a Minitab worksheet.

Step 2: Click “Stat”, then click “Basic Statistics,” then click “Descriptive Statistics.”

Step 3: Click the variables you want to find the variance for and then click “Select” to move the variable names to the right window.

Step 4: Click “Statistics.”

Step 5: Check the “Variance” box and then click “OK” twice. The variance in Minitab will be displayed in a new window. The variance for this particular data set is 540.667.

That’s it!

Tip: Check out our online standard deviation and variance calculator!

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If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.

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Variance in Minitab: How to Find it was last modified: October 12th, 2017 by Stephanie Glen

2 thoughts on “Variance in Minitab: How to Find it

  1. Allen

    Hello, just a suggestion that you may want to clarify that the variance of 540.67 is actually the variance for a SAMPLE distribution rather than a POPULATION distribution while the formula you show in the article is for a POPULATION data distribution. Sample variances are similar to population variances with the difference being that the former has a denominator of (N-1) to account for some uncertainty regarding a population parameter in a sample distribution while the latter has a denominator of (N) as shown above. The population variance of your data set above is 506.88. Thank you for your article!