Lecture 24

# Lecture 24 - Nonparametric Statistics All of the hypothesis...

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Nonparametric Statistics: All of the hypothesis testing methods we have covered up to this point assume that the data follows a certain distribution, generally the normal distribution. These are considered to be parametric methods . In real life, data sometimes fails to meet this assumption. Several methods have been developed to test data without assuming any knowledge of the distribution of the underlying populations, except that they are continuous. These methods are called nonparametric or distribution-free methods .

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ONE SAMPLE TESTS 1) Sign Test: This method is used when we want to test Ho: 0 ~ ~ μ = and n<30 and the population is not normal. Assumption: X 1 , X 2 , X 3, , X n are independently and identically distributed. Our hypotheses can be one-sided or two-sided: Ho: 0 ~ ~ = H1: 0 ~ ~ or 0 ~ ~ μ< or 0 ~ ~ μ≠ Calculating the Test Statistic: Find D i =X i - μ 0 for each sample value. If we get any D i =0, remove that from the sample and decrease the sample size by 1 for each D
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## This note was uploaded on 02/15/2009 for the course STAT 2004 taught by Professor Melutz during the Fall '07 term at Virginia Tech.

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Lecture 24 - Nonparametric Statistics All of the hypothesis...

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