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153 Non-Parametric Equivalents of the t -test In the event that one is working on the data that does not fulfill the requirements for a parametric test (i.e. if the data are not normally distributed; if the variances for the two conditions are markedly different; or if the data are measurements on an ordinal scale) there are options to use tests that do not adhere to the strict assumptions of parametric tests. The nature of the data will determine the exact tests to use. It is safer to use the less strict tests called non-parametric tests in SPSS to explore and analyse the data because parametric tests cannot be performed due to some limitations. The Mann-Whitney - This test is used when two different groups of participants have at least two conditions. Thus, it is appropriate for analysing the data from an independent-measures design with two conditions. The logic behind the Mann-Whitney test is to rank the data for each condition, which assesses differences in the two rank totals. If there is a systematic difference between the two conditions, then most of the high ranks will belong to one condition and most of the low ranks will belong to the other one. As a result, the rank totals will be quite different. On the other hand, if the two conditions are similar, then high and low ranks will be distributed fairly evenly between the two conditions and the rank totals will be fairly similar. The Mann-Whitney test statistic " U " reflects the difference between the two rank totals. The SMALLER it is (taking into account how many participants are in each group) the less likely it is to have occurred by chance. A table of critical values of U shows how likely it is to obtain the particular value of U purely by chance (Note that the Mann-Whitney test is unusual in this respect: normally, the BIGGER the test statistic, the less likely it is to have occurred by chance). Performing Mann-Whitney in SPSS 1. Go to Analyse 2. Non-parametric Tests 3. Legacy Dialogs 4. 2 independent samples and click. 5. The 2 independent samples dialog will appear. 6. Enter the variables into the required boxes and click OK. The output generated gives information on the calculated value of U for the Mann-Whitney U test, and among other generated statistics, it will give the significance value that shows whether the difference exists or it is by chance.