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Unformatted text preview: Chapter 16 The ChiSquare Statistic PowerPoint Lecture Slides Essentials of Statistics for the Behavioral Sciences Seventh Edition by Frederick J. Gravetter and Larry B. Wallnau Chapter 16 Learning Outcomes Concepts to review • Proportions (math review, Appendix A) • Frequency distributions (Chapter 2) 16.1 Parametric and nonparametric statistical tests • Hypothesis tests used thus far tested hypotheses about population parameters • Parametric tests share several assumptions – Normal distribution in the population – Homogeneity of variance in the population – Numerical score for each individual • Nonparametric tests are needed when the research situation does not conform to the requirements of parametric tests. ChiSquare and other nonparametric tests • Do not state the hypotheses in terms of a specific population parameter • Make few assumptions about the population distribution – Often termed distribution free tests • Participants usually classified into categories – Nominal or ordinal scales are used – Data for nonparametric tests are frequencies 16.2 ChiSquare Test for Goodness of Fit • Uses sample data to test hypotheses about the shape or proportions of a population distribution. • Tests the fit of the proportions in the obtained sample with the hypothesized proportions of the population. Null hypothesis for Goodness of Fit • Specifies the proportion (or percentage) of the population in each category. • Rationale for null hypotheses: – No preference among categories. – No difference in one population from the proportions in another known population Figure 16.1 Distribution of eyecolor for a sample of n = 40 Data for the Goodness of Fit Test • In a sample of data, individuals in each category are counted....
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This note was uploaded on 04/08/2011 for the course PSY 216 taught by Professor Cynthiaingle during the Spring '11 term at KCTCS.
 Spring '11
 CynthiaIngle
 Psychology

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