Lab10_chi - Lab10 Chisquare 2 LearningObjectives

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    Lab 10 Chi-square   2 χ
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    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
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    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
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    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  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.
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    Goodness-of-Fit Example (1) Do the number of wins vary by starting lane? Lane 1 2 3 4 5 Wins 13 5 6 4 N= 30 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.   
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  G-o-F Example (2) Lane 1 2 3 4 5 Wins 13 5 6 4 N= 30 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. To calculate chi-square, use 
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This note was uploaded on 05/21/2011 for the course PSY 3213 taught by Professor Staff during the Fall '08 term at University of South Florida.

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Lab10_chi - Lab10 Chisquare 2 LearningObjectives

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