# slides_4 - Chapter 4 Nonparametric Methods For the rest of...

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Chapter 4 Nonparametric Methods

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For the rest of the semester, we’ll be discussing different ways to analyze data with a The methods you’ve seen before for dealing with a quantitative re- sponse variable have always assumed that the We’ll make that same assumption for some methods we’ll learn about in later chapters, but in this chapter we’ll learn about meth- ods that make almost no distributional assumptions. We call these
The name “nonparametric” comes from the fact that traditional statistical methods assume that the response variable has some dis- tribution ( ) and then try to say some- thing about the parameters ( ) that describe that distribution. Nonparametric methods work an entirely different way. After we discuss some general ideas in the first section of this chapter, the following section will cover different nonparametric hy- pothesis testing procedures, each of which corresponds to a tradi- tional hypothesis test that you learned about in your previous course:

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The Mann-Whitney U test is a nonparametric version of the The Wilcoxon signed-ranks test is a nonparametric version of the
4.1 Comparison to Traditional Methods What should we consider when choosing between a traditional method or a nonparametric method? Nonparametric methods typically work by ranking all the and then looking at the ranks of the observations rather than the actual values This causes nonparametric methods to work better than traditional methods in certain situations.

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Non-Normality and Small Samples
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