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 (a) Determine the coefficient of determination, r2, and interpret its meaning. (b) Determine the standard error of the estimate (Syx). (c) How useful do you think this regression model is for predicting the monthly rent? (d) Can you think of other variables that might explain the variation in monthly rent?
Independent variable, X: Size
Dependent variable, Y: Rent
Following table shows the calculations:
X | Y | X^2 | Y^2 | XY | |
850 | 1950 | 722500 | 3802500 | 1657500 | |
1450 | 2600 | 2102500 | 6760000 | 3770000 | |
1085 | 2200 | 1177225 | 4840000 | 2387000 | |
1232 | 2500 | 1517824 | 6250000 | 3080000 | |
718 | 1950 | 515524 | 3802500 | 1400100 | |
1485 | 2700 | 2205225 | 7290000 | 4009500 | |
1136 | 2650 | 1290496 | 7022500 | 3010400 | |
726 | 1935 | 527076 | 3744225 | 1404810 | |
700 | 1875 | 490000 | 3515625 | 1312500 | |
956 | 2150 | 913936 | 4622500 | 2055400 | |
1100 | 2400 | 1210000 | 5760000 | 2640000 | |
1285 | 2650 | 1651225 | 7022500 | 3405250 | |
1985 | 3300 | 3940225 | 10890000 | 6550500 | |
1369 | 2800 | 1874161 | 7840000 | 3833200 | |
1175 | 2400 | 1380625 | 5760000 | 2820000 | |
1225 | 2450 | 1500625 | 6002500 | 3001250 | |
1245 | 2100 | 1550025 | 4410000 | 2614500 | |
1259 | 2700 | 1585081 | 7290000 | 3399300 | |
1150 | 2200 | 1322500 | 4840000 | 2530000 | |
896 | 2150 | 802816 | 4622500 | 1926400 | |
1361 | 2600 | 1852321 | 6760000 | 3538600 | |
1040 | 2650 | 1081600 | 7022500 | 2756000 | |
755 | 2200 | 570025 | 4840000 | 1661000 | |
1000 | 1800 | 1000000 | 3240000 | 1800000 | |
1200 | 2750 | 1440000 | 7562500 | 3300000 | |
Total | 28383 | 59660 | 34223535 | 145512350 | 69863210 |
Sample size: n=25
Now,
(a)
The coefficient of determination, r2, is
It shows that 72.7% of variation in dependent variable rent is explained by independent variable size.
(b)
The standard error of estimate will be
(c)
R-square is close to 1 so it shows that model is useful. The standard error of estimate is large which shows that model is not very useful.
(d)
Yes other factor may be whether parking space available or not, location of building etc.