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Unformatted text preview: 1 Lab 10 Chi-square 2 χ Learning Objectives ¡ State the difference between the parametric and nonparametric statistical tests ¡ Compute and interpret correctly chi- square tests by hand for ¡ The goodness-of-fit test ¡ The test of independence ¡ Compute and interpret correctly both types of test using SPSS Nonparametric Tests ¡ The tests we have considered (t- test, ANOVA, correlation) are based on estimated parameters (estimates of and ). ¡ Nonparametric tests do not estimate parameters in order to compute probabilities. The null doesn’t need a parameter to find probabilities. µ ρ 2 The Goodness-of-fit Test 2 χ Use this (GoF) when you have a single categorical variable, as in the above examples. Chi-square is used for testing hypotheses about frequencies. Are there equal numbers of men and women students at USF? Do certain color M&Ms appear more often than other colors? Example: A sports psychologist wants to know if a starting lane results in more wins for a horse race. He collects data from a track. Goodness-of-Fit Example (1) Do the number of wins vary by starting lane? N= 30 2 4 6 5 13 Wins 5 4 3 2 1 Lane Alpha =.05. The null is that the frequencies are equal across lanes in the population. Alt: some lanes different. To calculate the test, we have to estimate frequencies under the null. G-o-F Example (2) N= 30 2 4 6 5 13 Wins 5 4 3 2 1 Lane If the null is true, we expect equal frequencies in each lane. We have 30 winners and 5 lanes. We expect 30/5 = 6 winners per lane....
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- Fall '08