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Unformatted text preview: It is used to analyze data recorded on a nominal scale (i.e., frequency counts inside separate categories) E.g., Frequency count of male and female students that buy Pepsi or Coke to test if there is a gender difference in soft drink preferences there are two forms of Chi 2 test: (1) Goodness of fit test (2) Independence test Chi Chi 2 2 statistical test statistical test Assumptions for Chisquare tests: Assumptions for Chisquare tests: all observations are independent (i.e., one frequency count per subject) expected frequency for any category is not less than 5 ChiSquare: Goodness of fit ( ChiSquare: Goodness of fit ( one one variable variable ) ) It compares a distribution of frequencies that were obtained from a sample to the distribution in a population as specified by the null hypothesis. Example: A researcher would like to explore what types of computers are preferred by students PC or Mac. 100 high school students were interviewed and the results showed that 40 students prefer Mac and 60 students prefer PC. Does the results indicate a significant preference of PC computers among high school students? Formulate null hypothesis To explore computer preferences among students  PC or Mac the null hypothesis predicts no difference in preferences = 50 % of students will prefer Mac and 50% of students will prefer PC ( this is a % base for your expected frequencies ) f e = % * n/100 f e = expected frequencies...
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This note was uploaded on 11/12/2009 for the course PSY 3301 taught by Professor Staff during the Fall '08 term at Texas State.
 Fall '08
 staff

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