You are shopping for a house in some city. You think about factors that could influence the price of the house and you come up with the following: Number of bedrooms (BR) Number of bathrooms (BATH) Whether or not the house is located in what is perceived as the best school district in the area (here SCHOOL = 1 if the house is in the good school district and SCHOOL = 0 if not) The number of square feet of living space (SQFT) You then do some research and find the recent sales data below. BR BATH SCHOOL SQFT PRICE 3 2 1 1100 88000 2 1 0 1100 48900 3 2 1 1600 109800 4 3 1 1800 151100 3 2 1 2100 147900 5 3 1 2600 169300 2 1 0 1000 12700 2 2 1 900 90600 4 2 1 1400 143800 3 2 0 1000 56500 2 2 0 900 72400 2 1 0 800 32400 3 1 0 1100 26100 2 1 0 1200 60900 3 1 0 1400 69100 The regression line which predicts house price from all 4 predictor variables is PRICE= *BR + *BATH + *SCHOOL + *SQFT + These 4 predictor variables explain what percent of the variation in house prices? percent Now, throw out the predictor BR and repeat. The regression line which predicts house price from the remaining three predictor variables is PRICE= *BATH + *SCHOOL + *SQFT +
You are shopping for a house in some city. You think about factors that could influence the price of the house and you come up with the following:
Number of bedrooms (BR)
Number of bathrooms (BATH)
Whether or not the house is located in what is perceived as the best school district in the area (here SCHOOL = 1 if the house is in the good school district and SCHOOL = 0 if not)
The number of square feet of living space (SQFT)
You then do some research and find the recent sales data below.
| BR | BATH | SCHOOL | SQFT | PRICE |
| 3 | 2 | 1 | 1100 | 88000 |
| 2 | 1 | 0 | 1100 | 48900 |
| 3 | 2 | 1 | 1600 | 109800 |
| 4 | 3 | 1 | 1800 | 151100 |
| 3 | 2 | 1 | 2100 | 147900 |
| 5 | 3 | 1 | 2600 | 169300 |
| 2 | 1 | 0 | 1000 | 12700 |
| 2 | 2 | 1 | 900 | 90600 |
| 4 | 2 | 1 | 1400 | 143800 |
| 3 | 2 | 0 | 1000 | 56500 |
| 2 | 2 | 0 | 900 | 72400 |
| 2 | 1 | 0 | 800 | 32400 |
| 3 | 1 | 0 | 1100 | 26100 |
| 2 | 1 | 0 | 1200 | 60900 |
| 3 | 1 | 0 | 1400 | 69100 |
The regression line which predicts house price from all 4 predictor variables is
PRICE= *BR + *BATH + *SCHOOL + *SQFT +
These 4 predictor variables explain what percent of the variation in house prices? percent
Now, throw out the predictor BR and repeat.
The regression line which predicts house price from the remaining three predictor variables is
PRICE= *BATH + *SCHOOL + *SQFT +
It is required to obtain the regression equation to predict the house price, first by considering all 4 predictor variables, then by considering only 3 predictor variables after dropping BR.
Step by step
Solved in 4 steps with 7 images
