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Levin and Fox Chapter 12. Statistics for Nonparametric Measures. Parametric measures. All of the statistical tests we have examined thus far require: Interval level data Normality in the population (or at least large samples so that the sampling distribution of means is normal).
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Levin and Fox Chapter 12 Statistics for Nonparametric Measures
Parametric measures • All of the statistical tests we have examined thus far require: • Interval level data • Normality in the population (or at least large samples so that the sampling distribution of means is normal)
Nonparametric tests What about social researchers who cannot employ a parametric test, that is, who either cannot…. • Assume normality? • Does not work with large numbers of cases? • Not using measures that are interval?
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.
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)
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