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Understanding Non-Parametric Methods
CAMS - University of Cambridge
A one-day course introducing a variety of non-parametric methods. Many of the most familiar statistical tests, such as the t-test, make assumptions about the distribution of the outcome of interest. Sometimes these assumptions will not be met, for example if the outcome is very skewed or the sample size small, in such cases using a parametric test may give misleading results.
Course Aims, to teach:
1.What non-parametric methods are
2.When to use non-parametric methods
3.Why non-parametric methods are not used more frequently
4.How to use and interpret non-parametric methods
By the end of the course, you should:
•Know that parametric tests are not always appropriate
•Know about the most commonly used non-parametric methods
•Be able to interpret computer output from SPSS®
•Be able to report results from non-parametric tests
•Have a useful handbook for future reference
Course Aims, to teach:
1.What non-parametric methods are
2.When to use non-parametric methods
3.Why non-parametric methods are not used more frequently
4.How to use and interpret non-parametric methods
By the end of the course, you should:
•Know that parametric tests are not always appropriate
•Know about the most commonly used non-parametric methods
•Be able to interpret computer output from SPSS®
•Be able to report results from non-parametric tests
•Have a useful handbook for future reference
