Running a Mood test to compare medians with XLSTAT

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

 The data are from a study where four different methods of growing corn are analyzed. This aims at assessing the yield per acre. These data have already being used in the book of Conover [Conover W.J. (1999). Practical Nonparametric Statistics, 3rd edition,Wiley].

Our goal is to test if the medians are the same whatever the method of growing.

Setting up a Mood test on k independant samples

After opening XLSTAT, select the XLSTAT / Non parametric tests / Comparison of 2 or more medians (Mood test) command, or click on the corresponding button of the Non parametric tests toolbar.

 Mood menu

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

The format of the dataset is such that you have one variable per sample. The option One column per variable can be used when data are in one column and the labels in another one.

Mood dialog box general

In the Options tab, three approaches are proposed to calculate/estimate the p-value. The significance level α can also be modified. Here, we leave the default options, i.e. a significance level α=5% and the asymptotic approach to estimate the p-value.

Mood dialog box options

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

Interpreting the results of a Mood test

The first results displayed are the statistics for the various samples. Next, the results of the Mood test and the multiple pairwise comparisons are displayed.

Hereafter are the Mood test results for the available dataset. Since the p-value is under the significance level (5%), the null hypothesis can be rejected.

Mood test results

Other options such as multiple comparisons using Mood test are also available in XLSTAT.

About KCS

Kovach Computing Services (KCS) was founded in 1993 by Dr. Warren Kovach. The company specializes in the development and marketing of inexpensive and easy-to-use statistical software for scientists, as well as in data analysis consulting.

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