Different statistical analyses are appropriate for different types of data. It is essential that you select the appropriate statistical test, because an incorrect test can result in incorrect research conclusions. Basically there are two types of statistical tests: parametric and nonparametric. Your first decision when selecting a statistical test is to determine whether a parametric or nonparametric test is appropriate. The use of a parametric test requires that three assumptions be met: the variable measured is normally distributed in the population, the data represent an interval or ordinal scale, and the selection of participants is independent. Most variables examined in social science research are normally distributed. Most measures used in social science research represent an interval scale. And the use of random sampling will fulfill the assumption of independent selection of participants. A nonparametric test is an appropriate statistical test to use when the three parametric assumptions are not met and when the data represent an ordinal or nominal scale.
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