parent nodes: Choosing a statistical test | index | IndexTools | non parametric | One way Anova | Sample size Calculations | Support | Whatsnew | What to do with not normally distributed Data


Kruskal-Wallis Test

Main Help

Tools
Proportions
Chi Square test
One way Anova
Kruskal-Wallis Test
Variation Levene test
Multiple Correlation
Multiple linear Regression
Generate Distribution
Calculations
Filter
Box-Cox transformation
Gauge R&R
Distribution fitting
Graphs


Full version of Develve
For commersial use
75 EURO

The Kruskal-Wallis calculates if the Median of two or more data sets at least one data-set is significant different. The calculation calculates the test only from the checked data sets in the Kruskal-Wallis dialogue. This is the non parametric counterpart of the One way Anova test is for not normally distributed data but before using this test try to find out why the data is not normally distributed.



Interpretation

For a good result the data must

Colors of the cells

Formula

All selected data-sets are sorted and ranked in order. The sum of the ranks of each data-set is calculated (formula)

formula

With tie correction

Ties are data point with the same value.
formula
With the H and the amount of df-1 value the p value can be calculated with the formula distribution.

Sample size

Sample size calculation is the same as with the One way Anova but with 15% more samples.
The result is the minimum sample size for all the data sets.

Legend

formula = Mean of ranks of group j
formula = Mean of ranks all ranks of all groups
formula = Amount of samples of group j
formula = total Amount of samples
formula = amount of ties of a rank
formula = degrees of freedom (amount of groups)

Example

From the selected data-sets there is at least one data-set that is significant different median compared to the other data sets.

Data file

External links