For this assignment you may use any data set you want as long as the one you choose contains at least one binary variable you can use as a dependent variable.
Directions: Choose at least two independent variables from your data set and one binary dependent variable. Please explain why you think each of your independent variables has a causal effect on your dependent variable.

1.      Please state the null hypothesis associated with each of your independent variables.

2.      Please state the alternative hypotheses associated with your independent variables as well as whether each one is a one or two—tailed test.

3.      Run a logistic regression model in Stata (or Gretl if you’re using that) which includes the independent and dependent variables you chose earlier.

4.      Interpret the odds ratio for each of your independent variables and state whether each one is statistically significant or not.

5.      Interpret the confidence interval for each of the odds ratios referred to in question 4 and explain how your confidence interval findings are related to your findings regarding statistical significance.

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The dependent variable is an indication of whether the particular mother has more than or equal to 3 kids in the family. The logistic regression model tries to analyze how the mother’s age, whether the first child is boy or not, and whether the second child is boy or not affects this probability. It is expected that the higher age will have a negative effect on morekids because of the physical limitation. It is absolutely uncertain on what kind of impact other two variables will have on morekids.
The null hypothesis of each variable: agem1, boy1st and boy2 is that the coefficient of the each variable is zero. Let the coefficient for agem1 is β_1. Then, the null hypothesis is β_1=0 . Let the coefficient for boy1st and boy2nd be β_2 and β_3 respectively. Then, their null hypotheses are β_2=0 and β_3=0 respectively....


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