August+11th+slides - Quantitative Methods in Psychology...

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Chi-square: The final lecture August 11 th 2009 Jeffrey Vietri Quantitative Methods in Psychology
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Today’s Agenda Learn some Chi-square stuff Non-parametric hypothesis test It’s what we do with nominal data! Review homework questions from Ch 15 Mention that I’ll be here at 9:30am tomorrow Remind you that the final is at 11:00am tomorrow
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Parametric versus Non- parametric Z-test, t-test, ANOVA, r, all are parametric tests Parametric tests: Test hypothesis about population parameters (characteristics of the population: μ , σ 2 , ρ , etc). Requires assumptions about parameter (e.g. normality, homogeneity of variance). What if data can’t be described in terms of means and variances (if you have nominal or ordinal variables), or when parameter assumptions are violated?
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Chi-square ( χ 2 ) test Is a non-parametric test. χ 2 tests analyze frequencies associated in categories to determine if the proportion of people in one category is more than another in the population Difference in the nature of the data: For χ 2 tests: frequencies— count of how many individuals are in each category For parametric tests: numerical scores (interval or ratio) – value of some measure in each individual
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Two types of χ 2 tests Goodness-of-fit Tests how well the obtained sample proportions fit the population proportions specified by null hypothesis. Test of independence
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This note was uploaded on 11/17/2011 for the course PSYCHOLOGY 830:200 taught by Professor Staff during the Fall '11 term at Rutgers.

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August+11th+slides - Quantitative Methods in Psychology...

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