week 7 question 1 2.docx

# Non parametric tests should be used when the data has

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parametric test. Non parametric tests should be used when the data has an abnormal distribution, is complex and non linear. (Changing Minds, 2018) Two reasons to use a non parametric test:

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1. Sample size is ≤ 30. "The parametric assumption of normality is particularly worrisome for small sample sizes (n < 30). Nonparametric tests are often a good option for these data" (Hoskins, 2018). 2. The non parametric test is more simplistic compared to the parametric test, and "less affected by outliers" (Changing Minds, 2018). Overall, its best to use parametric testing when the data given is linear, and normally distributed based on the mean and standard deviation, fitting within the parameters of the parametric tests. It is best to use non parametric testing when the data given is non linear, abnormally distributed based on the median, and does not fit within the parameters of the parametric tests. References Changing Minds. Parametric vs. non-parametric tests. (2018). Retrieved from Hoskin, T. (n.d.). Parametric and Nonparametric: Demystifying the Terms. Retrieved from question 7 2 teacher question Veronica,
Can you provide an example where a nonparametric test is used? Also, can you list the type of
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• Fall '14
• dargon
• Non-parametric statistics, parametric tests, Boston University School of Public Health, Hoskins, Dr.J

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