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Cochran C test to detect outlying variances tutorial

2016-05-04

This tutorial will help you run a Cochran C test to detect outlying variances and interpret the results in Excel using XLSTAT.

Dataset for testing variances with a Cochran C test

An Excel sheet with both the data and the results can be downloaded by clicking here.

Four samples have been obtained from two different distribution: 3 with a normal distribution with mean 0 and variance 2 and one with a normal distribution with mean 0 and variance 5 .We wish to test if there is a variance larger than the others

Goal of this tutorial

We would like to detect if a variance is larger than the others using the Cochran C test.

Setting up a Cochran C test to detect an outlying variance

To start the Cochran C test go to the menu Testing outliers / Cochran's C test.

cochran c test menu

In the General tab, select the data. Four columns should be selected with the option one column per group. Since the number of observation per sample are equal, we use the balanced option.

cochran c test dialog box general

As an alternative hypothesis choose the two-sided option. The default significance level is left as is: 5%.

cochran c test dialog box options

When ready click on OK.

Results of a Cochran C test

The result is that the p-value for this test is smaller than 0.0001. That means that the null hypothesis should be rejected.

cochran test result

In the following table, the detected variances and outliers are given.

cochran test outlier

Then, a graphic with all variances represented is displayed.

cochran test graph

We have shown that there is an outlying variance in our dataset.

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