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Though nonparametric statistical tests have more flexibility than do parametric statistical tests, nonparametric tests are not as robust; therefore, most statisticians recommend that when appropriate, parametric statistics are tric and nonparametric table below outlines some common research designs and their appropriate parametric and nonparametric equivalents. While i understand the basics and even the more advanced statistics, i’m not great at applying them or interpreting the data.
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Prior to running any parametric statistics, you should always be sure to test the assumptions for the tests that you are planning to ametric implied by the name, nonparametric statistics are not based on the parameters of the normal curve. The study also examined the relationships between the research methods and statistical analysis techniques students used in their dissertation and the type of doctoral degree they obtained.
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Sticking to a rigid plan for which statistics test to use that you made before you obtained your data can be very dangerous in terms of the validity of your entire project, because that plan may no longer apply to your data, especially if your hypothesis is very different from what you common issues with statistical procedures that you should consider include limited number of participants, limited number of cases across groups, and violations of normality of key variables. Because parametric statistics are based on the normal curve, data must meet certain assumptions, or parametric statistics cannot be calculated.