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5 Cards in this Set
- Front
- Back
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uses sample data to test hypotheses about the shape or proportions of a population distribution. The test determines how well the obtained sample proportions fir the population proportions specified by the null hypothesis |
chi-square test for goodness of fit |
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the number of individuals from the sample who are classified in a particular category Each individual is counted in one and only one category. |
observed frequency |
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the frequency value that is predicted from the proportions in the null hypothesis and the sample size. The expected frequencies define ideal, hypothetical sample distribution that would be obtained if the sample proportions were in perfect agreement with the proportions specified in the null hypothesis |
expected frequency |
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uses the frequency data from a sample to evaluate the relationship between two variables in the population. Each individual in the sample is classified on both of the two variables, creating a two-dimensional frequency-distribution matrix. The frequency distribution for the sample is then used to test hypotheses about the corresponding frequency distribution for the population |
chi-square test for independence |
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this is when there is no consistent, predictable relationship between them. In this case, the frequency distribution for one variable is not dependent on the categories of the second variable. As a result, when two variables are independent, the frequency distribution for one variable has the same shape for all categories of the second variable |
independent |
