MATH 321 Lecture Notes - Lecture 68: Null Hypothesis, Contingency Table, Regional Policy Of The European Union
22 Jul 2019
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Learning objective: perform a test for independence, perform a test for homogeneity of proportions. 12. 2. 1 perform a test for independence (1 of 36) The chi-square test for independence is used to determine whether there is an association between a row variable and column variable in a contingency table constructed from sample data. The null hypothesis is that the variables are not associated; in other words, they are independent. The alternative hypothesis is that the variables are associated, or dependent. 12. 2. 1 perform a test for independence (2 of 36) In a chi-square independence test, the null hypothesis is always h. 12. 2. 1 perform a test for independence (3 of 36) The idea behind testing these types of claims is to compare actual counts to the counts we would expect if the null hypothesis were true (if the variables are independent). If a significant difference between the actual counts and expected counts exists, we would take this as evidence against the null hypothesis.
