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    Chi-square goodness-of-fit-test vs independent t-test

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    This week introduces the chi-square goodness-of-fit-test, which looks for differences across independent groups. Since this is similar to the independent t-test, which looks for differences between independent groups,

    1). Discuss what each of these tests is actually measuring.

    2). Be sure that your discussion addresses the major differences between each of these approaches.

    3). How do you know when to use one analysis over the other?

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    1). Discuss what each of these tests is actually measuring.

    A chi-square is a test to see if observed frequencies are different from expected frequencies. It is used with ordinal or nominal variables. It can be used to test goodness-of-fit or independence across groups. Since it is a parametric test, it does not require the sample data to be normally distributed but it does assume the variable is normally distributed in the population.

    The goodness-of-fit compares the observed frequencies to a theoretical distribution. The test for independence tests a contingency table. It tests the frequencies of one variable for different values of another nominal variable. This is similar to finding an ...

    Solution Summary

    Your tutorial is 377 words plus three references and gives examples in everyday language and a 2 x 2 contingency table to illustrate.