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Durbin-Watson test in Excel tutorial

2016-05-13

This tutorial will help you set up and interpret a Durbin-Watson test to detect autocorrelation in Excel using the XLSTAT software.

Dataset for running the Durbin-Watson test

The data have been obtained in Lewis T. and Taylor L.R. (1967). Introduction to Experimental Ecology, New York: Academic Press, Inc.. They concern 237 children, described by their gender, age in months, height in inches (1 inch = 2.54 cm), and weight in pounds (1 pound = 0.45 kg).

We have run a simple linear regression between the height and the weight to get the residuals.

Goal of this tutorial

 Using Durbin-Watson test, we want to detect if the residuals from a linear regression are autocorrelated or not.

Setting up a Durbin-Watson test

After opening XLSTAT, select the XLSTAT / Time / Durbin-Watson test command.

Once you've clicked on the button, the dialog box appears.

Select the data on the Excel sheet. In our case, the residuals are obtained via the linear regression between the height and the weight and the explanatory variable is the "Height".

As the column header was selected for the variables, the Variable labels option needs to be activated.

Durbin-Watson test data

On the Options tab, the user can set the significance level of the test and the order (number of lags). Here we choose to leave the default values.

Durbin-Watson test significance level

The computations begin once you have clicked on OK. The results will then be displayed in a new sheet.

Interpreting the results

The first results displayed are the statistics for the residuals. Next the results of the Durbin-Watson test and a short interpretation are displayed.

Durbin-Watson test results

Since the p-value is greater than the significance level (5%), the null hypothesis cannot be rejected.

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