In: Statistics and Probability
An agent for a residential real estate company in a large city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward that goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sample of 25 apartments in a particular residential neighborhood and collects the following data:
Size (square feet) |
Rent ($) |
850 |
1950 |
1450 |
2600 |
1085 |
2200 |
1232 |
2500 |
718 |
1950 |
1485 |
2700 |
1136 |
2650 |
726 |
1935 |
700 |
1875 |
956 |
2150 |
1100 |
2400 |
1285 |
2650 |
1985 |
3300 |
1369 |
2800 |
1175 |
2400 |
1225 |
2450 |
1245 |
2100 |
1259 |
2700 |
1150 |
2200 |
896 |
2150 |
1361 |
2600 |
1040 |
2650 |
755 |
2200 |
1000 |
1800 |
1200 |
2750 |
Make a Normal Probability Plot and a Residual plot of the Residuals (Y axis) vs. Apartment Size (X axis). Based on these results, evaluate whether the assumptions of regression have been seriously violated.