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Unformatted text preview: Chapter 4 Nonparametric Methods 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: • The MannWhitney U test is a nonparametric version of the • The Wilcoxon signedranks 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. ◯ NonNormality and Small Samples Many traditional procedures that assume a normal distribution for...
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This note was uploaded on 03/27/2012 for the course STA 3024 taught by Professor Ta during the Spring '08 term at University of Florida.
 Spring '08
 TA
 Statistics

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