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الدرس 79
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Lesson 79
SPSS
v.23
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Difference between
Mann-Whitney U Test & Kolmogorov-Smirnov Z test
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The Kolmogorov-Smirnov test assesses the hypothesis that two samples were drawn from different populations. Unlike the parametric t-test for independent samples or the Mann-Whitney U test, which test for differences in the location of two samples (differences in means, differences in average ranks, respectively), the Kolmogorov-Smirnov test is also sensitive to differences in the general shapes of the distributions in the two samples (i.e., to differences in dispersion, skewness, etc.).
So, The main difference between U & KS Test is:
Mann-Whitney U Testing for differences in location
& Kolmogorov-Smirnov Z Testing for differences in shape
Testing for equality of distributions
H0: Both samples come from a population with the same distribution
Ha: There is a significant difference between the distributions for the samples.
We have 3 types of Kolmogorov-Smirnov test:
1- Testing for Normality.
2- Testing for Goodness-of-fit :to check if a certain set of continuous values follows a certain theoretical distribution.
3- Testing for two-sample KS: a nonparametric hypothesis test that measures the probability that a chosen univariate dataset is drawn from the same parent population as a second dataset.
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15 min.
22-1-2017
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