Kruskal-Wallis non-parametric ANOVA
the data points must be independent from each other
the distributions do not have to be normal and the variances do not have to be equal
you should ideally have more than five data points per sample
all individuals must be selected at random from the population
all individuals must have equal chance of being selected
sample sizes should be as equal as possible but some differences are allowed
if you do not find a significant difference in your data, you cannot say that the samples are the same
if significant differences are found when comparing more than two samples there are non-parametric multiple comparison tests available but they are only found in UNISTAT and otherwise have to be performed manually or calculated long-hand in Excel.
Kruskal-Wallis compares between the medians of two or more samples to determine if the samples have come from different populations. For instance it is a well known aspect of natural history that the littorinid species (snails) that are found on sheltered and exposed shores have different shell morphologies. This could be tested by measuring the shell thickness of each individual in samples taken from a sheltered, an exposed and an intermediate shore. If the distributions prove not to be normal and/or the variances are different then the Kruskal-Wallis should be used to compare the groups. If a significant difference is found then there is a difference between the highest and lowest median. A non-parametric multiple comparison test must then be used to ascertain whether the intermediate shore also is significantly different. These are found in UNISTAT but must be set up on a spreadsheet in Excel or done by hand from the examples given in Zar (1984).
In the above example only one factor is considered (level of shore exposure) and so is termed a one-way Kruskal-Wallis. There are examples in Zar (1984) of a two-way Kruskal-Wallis test but again must be set up in Excel or done by hand.
Once you have established that your data suits Kruskal-Wallis, your data must be arranged thus for use in one of the statistical packages (SPSS, UNISTAT):
(Degrees of Freedom = number of samples/treatments - 1)
On completion of the 1-way Kruskal-Wallis the results will look something like this:
Although it looks a bit daunting do not be worried. There is only one value that concerns the selection of one of the hypotheses. The Right-Tail Probability (0.0052) is the probability of the differences between the data sets occurring by chance. Since it is lower than 0.05 the HO must be rejected and the HA accepted.
Two-way Kruskal-Wallis results would appear in a similar format to the two-way ANOVA.