This procedure is available in both the Analyse-it Standard and the Analyse-it Method Evaluation edition
Kruskal-Wallis test is a non-parametric test for a difference in central location (median) between two or more independent samples.
The requirements of the test are:
Data in existing Excel worksheets can be used and should be arranged in a List dataset layout or Table dataset layout. The dataset must contain a continuous scale variable and a nominal/ordinal scale variable containing two or more independent groups.
When entering new data we recommend using New Dataset to create a new 2 variables (1 categorical) dataset ready for data entry.
To start the test:
Excel 97, 2000, 2002 & 2003:
Select any cell in the range containing the dataset to analyse, then click Analyse on the Analyse-it toolbar, click Compare Groups then click Kruskal Wallis.
If the dataset is arranged using the list layout:Click Variable and select the dependent variable and click Factor and select the independent variable containing the groups to compare.
The report shows the number of observations analysed, and, if applicable, how many missing values were excluded. Summary statistics for the ranks of each sample are also shown.
The Kruskal-Wallis statistic and hypothesis test are shown. The p-value is the probability of rejecting the null hypothesis, that the samples have the same median, when it is in fact true. A significant p-value implies that at least two samples have different medians. To determine which samples differ perform multiple comparisons.
METHOD The p-value is calculated using the chi-square approximation with correction for ties (see ). When the number of observations are ≤ 25 it is recommended to lookup an exact p-value (see ).
Multiple comparisons allow pairs of groups to be compared to determine which are different. When comparing many groups the chance of committing a type I error increases. To reduce the risk multiple comparisons should only be made when the Kruskal-Wallis test is significant. The risk is further reduced with error protection methods:
METHOD See  and  for more information on how the multiple comparisons are calculated.
To calculate multiple comparisons:
The groups compared, the difference between mean ranks, and hypothesis test are shown. If the p-value is significant the group medians are different.
To disable multiple comparisons: