In: Statistics and Probability
An agent for a residential real estate company in a sub-urb located outside of Washington, DC, has the business objec-tive 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 48 one-bedroom apartments.
Interpret the meaning of b0 and b1 in this problem.
Size (Square feet) | Rent ($) |
524 | 1110 |
616 | 1175 |
666 | 1190 |
830 | 1410 |
450 | 1210 |
550 | 1225 |
780 | 1480 |
815 | 1490 |
1070 | 1495 |
610 | 1680 |
835 | 1810 |
660 | 1625 |
590 | 1469 |
675 | 1395 |
744 | 1150 |
820 | 1140 |
912 | 1220 |
628 | 1434 |
645 | 1519 |
840 | 1105 |
800 | 1130 |
804 | 1250 |
950 | 1449 |
800 | 1168 |
787 | 1224 |
960 | 1391 |
750 | 1145 |
690 | 1093 |
840 | 1353 |
850 | 1530 |
965 | 1650 |
1060 | 1740 |
665 | 1235 |
775 | 1550 |
960 | 1545 |
827 | 1583 |
655 | 1575 |
535 | 1310 |
625 | 1195 |
749 | 1200 |
634 | 1185 |
641 | 1444 |
860 | 1385 |
740 | 1275 |
593 | 1050 |
880 | 1650 |
895 | 1340 |
692 | 1560 |
Please use Excel. The only thing I cant figure out is b1
We have calculated the b0 and b1 using excel:
Go to Data tool-->data analysis -->Regression-->Select range of x and y respectively -->click on labels--->ok
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.354314 | |||||||
R Square | 0.125539 | |||||||
Adjusted R Square | 0.106529 | |||||||
Standard Error | 186.0407 | |||||||
Observations | 48 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 228565.2 | 228565.2 | 6.603807 | 0.013481 | |||
Residual | 46 | 1592112 | 34611.13 | |||||
Total | 47 | 1820677 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 992.9927 | 147.3669 | 6.738236 | 2.25E-08 | 696.3586 | 1289.627 | 696.3586 | 1289.627 |
Size (Square feet) | 0.493167 | 0.19191 | 2.569787 | 0.013481 | 0.106873 | 0.879461 | 0.106873 | 0.879461 |
Here,b0=999.9927
and b1=0.493167
The scatter plot between x and y is:
Here,b1 is the slope it shows the amount change in y when we change the one unit of x in the model.
The model is: y = 0.4932x + 992.99
Cheers!!