1) Describe the chi-square test of independence.
2) How is this test different from the chi-square goodness-of-fit test?
3) Are the assumptions underlying each of these tests the same?
4) When presented with nonparametric data how do you know which of these tests to use?
1). Describe the chi-square test of independence.
The chi-square test of independence checks for a relationship between two categorical variables. It basically tests a contingency table for two attributes (categorical variables). It will check to see if the second variables would be expected to change once you know the value of the first variable. In other words, it is looking to see if there is a conditional probability. For example, if you know someone is a female, does that change your guess about whether they will have a purse with them? Yes! Then "female" and "purse-carrying" are not independent. Sometimes you don't know if variables in a population are independent and so you want to test ...
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