1. The file midcity (shown as problem 4 on the template) contains data on 128 recent real-estate sales in Mid City. For each sale, the file shows the neighborhood (1, 2 or 3) in which the house is located, the number of offers made on the house, the square footage, whether the home has brick front or not, the number of bathrooms, the number of bedrooms, and selling price. Neighborhoods 1 and 2 are more traditional neighborhoods, whereas neighborhood 3 is newer, more prestigious neighborhood. Use multiple regression to interpret the pricing structure of houses in Mid City and answer the following questions (note , the first column in the MidCity file is home or sample number. Do not include this variable in the regression equation):
a. Comment on the models ability to predict price of the home based on the given variables. Is this a good predictor model? Why or why not?
b. Is there a relationship between the independent and dependent variables? Why or why not (test at alpha = .05)?
c. Comment on the contribution of each of the variables (including the intercept). State whether the variables (and intercept) contribute to the linear prediction of the model. Why or why not (test at alpha = .05)?
d. What should the selling price be for a house in neighborhood 3, with 3000 square feet, a brick front, 5 bedrooms, 3 bathrooms and 5 offers on the home?
2. Consider a large population of families in which each family has exactly three children. If the genders of the three children in any family are independent of one another, the number of male children in a randomly selected family will have a binomial distribution of three trials. Suppose a random sample of 160 families yields the following results:
Number of Male Children 0 1 2 3
Frequency 14 66 64 16
Conduct a test at a level of significance equal to .05 to determine if the observed frequencies in the data follow a binomial distribution