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Xlstat 2 variances9/5/2023 We can Assume equality for the variances as we just computed the test before.Īs can be seen in the results of this test, we conclude that there is significant difference between the two means, the sepal width of Versicolor iris being smaller than the sepal width of the Setosa iris. In the Options tab elect the alternative Mean 1 – Mean 2 < D where D is 0. Select the option Student’s test as we do not know the true variances of the populations. In the general tab do the same sample selection as previously for the sepal width. Go to the menu Parametric tests / Two-sample t-test and z-test One-tailed tests are generally more precise. Therefore we can run a one-tailed test for the test on the average. You can notice in the Descriptive statistic table that the mean of the sepal width for Versicolor is inferior to the mean of Setosa for the same characteristic. This time the variances can be considered as equal as the p-value of the test (0.189) is superior to 0.05.Īs the equality of variance (also called homoscedasticity) is assumed we can run a test of comparison of means. For Sample 1 enlighten the column C and for Sample 2 choose the column F. The only change in the procedure described above is the data selection. We are now going to do the same thing but for the sepal width. The two populations -Versicolor and Setosa - sepal length do not follow the same distribution. Hence the variances cannot be considered as equal. The results that appear in a new sheet show that the H0 hypothesis should be rejected as the p-value 0.009 is inferior to our limit of 5%. Results of a Fisher's F-test in XLSTAT to assess the equality of variance of 2 samples The other outputs can also be selected if wanted. We don’t have missing data so we can go directly to the tab Outputs and enable the option Descriptive statistics. The default significance level of 5% is to be kept. We want to test the equality of variance which means that the alternative hypothesis is : Variance 1 / Variance 2 ≠ R where R is 1. Once all these options are set we can move on to the tab Options. The test we decide to run is the Fisher’s F-test. We select the option Sheet to get the results in a new sheet of the workbook.Īs the columns have a label the option Column labels should be enabled. The Data format is One column per sample as each column corresponds to one of the samples. In the tab General select the data for the sample 1 and 2įor Sample 1 select the column B containing the sepal length for the variety Versicolor and for the Sample 2 the column E corresponding to the sepal length for the Setosa samples. The two-sample comparison of variances dialog box appears ![]() Go to the menu bar Parametric Tests / Two-sample comparison of variances. To realize a two-sample comparison of variances test : Setting up a Fisher's F-test in XLSTAT to assess the equality of variance of 2 samples If they are equals, we will be able to compare the averages. We can now launch a Fisher's test in order to test the equality of variance of the 2 samples. All 4 samples (Versicolor-Sepal length, Versicolor-Sepal width, Setosa-Sepal length, Setosa-Sepal width) follow a normal distribution. You will find those statistics computed in the Excel sheet. The first thing to do is to assess if the samples follow a Normal distribution as the Fisher F-test is sensitive to data that do not follow a normal distribution. We will then compare the distribution of these variables for the 2 samples. ![]() Our goal is to assess if there is a difference between the species for the sepal length and sepal width. ![]() There are two different species included in this example: setosa and versicolor. The data are from and correspond to the sepal characteristics of 100 Iris flowers described by two variables (sepal length, sepal width). Dataset for running a Fisher's F-test in XLSTAT to assess the equality of variance of 2 samples This tutorial will help you test the difference between two observed variances, using Fisher’s F test, in Excel using the XLSTAT software.
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