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Levin and Fox Chapter 12 Statistics for Nonparametric Measures.

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Presentation on theme: "Levin and Fox Chapter 12 Statistics for Nonparametric Measures."— Presentation transcript:

1 Levin and Fox Chapter 12 Statistics for Nonparametric Measures

2 Parametric measures 1.All of the statistical tests we have examined thus far require: a)Interval level data b)Normality in the population (or at least large samples so that the sampling distribution of means is normal)

3 Nonparametric tests What about social researchers who cannot employ a parametric test, that is, who either cannot…. a.Assume normality? b.Does not work with large numbers of cases? c.Not using measures that are interval?

4 Nonparametric tests Nonparametric tests make less stringent demands, but are less powerful tests than their parametric counterparts. An researchers is more likely to reject the null hypothesis when using a parametric test than when using a nonparametric test.

5 Examples of nonparametric tests One-Way Chi-Square (nominal data) Two-Way Chi-Square (nominal data – 2 variables) The Median Test (ordinal data) Spearman’s Rank-Order Correlation (ordinal) Goodman’s and Kruskal’s Gamma (ordinal) Phi coefficient (nominal – 2 variables) Contingency coefficient (nominal – more than 2)

6 Extra Credit Homework Two-Way Chi-Square (chapter 9) Convert Chi-Square into a Phi Coefficient (ch.12) Check your Chi-Square statistic using the chi- quare1.sav file on the webpage to check your work. Replaces a low scoring homework


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