A real estate developer wishes to study the relationship between the size of home a client will purchase (in square feet) and other variables. Possible independent variables include the family income, family size, whether there is a senior adult parent living with the family (1 for yes, 0 for no), and the total years of education beyond high school for the husband and wife. The sample information is reported below. Family Square Feet Income (000s) Family Size Senior Parent Education 1 2,240 60.8 2 0 4 2 2,380 68.4 2 1 6 3 3,640 104.5 3 0 7 4 3,360 89.3 4 1 0 5 3,080 72.2 4 0 2 6 2,940 114 3 1 10 7 4,480 125.4 6 0 6 8 2,520 83.6 3 0 8 9 4,200 133 5 0 2 10 2,800 95 3 0 6 Develop an appropriate multiple regression equation using stepwise regression. (Use Excel data analysis and enter number of family members first, then their income and delete any insignificant variables. Leave no cells blank - be certain to enter "0" wherever required. R and R2 adj are in percent values. Round your answers to 3 decimal places.) b. Select all independent variables that should be in the final model. (You may select more than one answer. Single-click the box with the question mark to produce a check mark for a correct answer and double-click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.) check all that apply Senior parent Square feet Family sizeunanswered Income Education c. Write out the regression equation. d. Report and interpret the adjusted R2.
A real estate developer wishes to study the relationship between the size of home a client will purchase (in square feet) and other variables. Possible independent variables include the family income, family size, whether there is a senior adult parent living with the family (1 for yes, 0 for no), and the total years of education beyond high school for the husband and wife. The sample information is reported below.
| Family | Square Feet | Income (000s) | Family Size | Senior Parent | Education | ||||||
| 1 | 2,240 | 60.8 | 2 | 0 | 4 | ||||||
| 2 | 2,380 | 68.4 | 2 | 1 | 6 | ||||||
| 3 | 3,640 | 104.5 | 3 | 0 | 7 | ||||||
| 4 | 3,360 | 89.3 | 4 | 1 | 0 | ||||||
| 5 | 3,080 | 72.2 | 4 | 0 | 2 | ||||||
| 6 | 2,940 | 114 | 3 | 1 | 10 | ||||||
| 7 | 4,480 | 125.4 | 6 | 0 | 6 | ||||||
| 8 | 2,520 | 83.6 | 3 | 0 | 8 | ||||||
| 9 | 4,200 | 133 | 5 | 0 | 2 | ||||||
| 10 | 2,800 | 95 | 3 | 0 | 6 | ||||||
Develop an appropriate multiple regression equation using stepwise regression. (Use Excel data analysis and enter number of family members first, then their income and delete any insignificant variables. Leave no cells blank - be certain to enter "0" wherever required. R and R2 adj are in percent values. Round your answers to 3 decimal places.)
b. Select all independent variables that should be in the final model. (You may select more than one answer. Single-click the box with the question mark to produce a check mark for a correct answer and double-click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.)
check all that apply
- Senior parent
- Square feet
- Family sizeunanswered
- Income
- Education
c. Write out the regression equation.
d. Report and interpret the adjusted R2.
Trending now
This is a popular solution!
Step by step
Solved in 3 steps with 2 images
