An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for apartments, based on the size of the apartment, as defined by square footage. A sample of eight apartments in a neighborhood was selected, and the information gathered revealed the data shown below. For these data, the regression coefficients are b0= 328.6794 and b1=0.8881. Complete parts (a) through (d).
Monthly Rent ($) | Size (Square Feet) |
925 | 750 |
1,500 | 1,250 |
850 | 900 |
1,450 | 1,250 |
1,950 | 2,000 |
950 | 650 |
1,825 | 1,300 |
1,350 | 1,100 |
Determine the coefficient of determination, r2 , and interpret its meaning. (round to three decimals)
Determine the standard error of the estimate, SYX (round to three decimals)
What is the meaning of SYX?
SYX measures the typical difference between an apartment's actual rent and the rent predicted by the regression equation.
SYX measures the typical difference between an apartment's size and the size predicted by the regression equation.
SYX measures the amount by which an apartment's rent is greater than the rent predicted by the regression equation.
SYX measures the amount by which an apartment's rent is less than the rent predicted by the regression equation.
Using Excel, go to Data, select Data Analysis, choose Regression. Put Monthly Rent in Y input range and Size in X input range.
SUMMARY OUTPUT | |||||
Regression Statistics | |||||
Multiple R | 0.900 | ||||
R Square | 0.809 | ||||
Adjusted R Square | 0.777 | ||||
Standard Error | 196.097 | ||||
Observations | 8 | ||||
ANOVA | |||||
df | SS | MS | F | Significance F | |
Regression | 1 | 978025.454 | 978025.454 | 25.434 | 0.002 |
Residual | 6 | 230724.546 | 38454.091 | ||
Total | 7 | 1208750.000 | |||
Coefficients | Standard Error | t Stat | P-value | ||
Intercept | 328.679 | 214.054 | 1.535 | 0.176 | |
Size | 0.888 | 0.176 | 5.043 | 0.002 |
Coefficient of determination (R-square) = 0.809
Standard error of the estimate = 196.07
SYX measures the typical difference between an apartment's actual rent and the rent predicted by the regression equation. (Option 1)
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