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Instruction 13 ANOVA Note: Adj R Square = Adjusted R Square; Std

question 112

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Instruction 13.16
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) , family size (Size) and education of the head of household (School) . House size is measured in hundreds of square metres, income is measured in thousands of dollars and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided below:
OUTPUT
SUMMARY
Regression Statistics
 Multiple R 0.865 R Square 0.748 Adj. R Square 0.726 Std. Error 5.195 Observations 50\begin{array} { l l } \text { Multiple R } & 0.865 \\ \text { R Square } & 0.748 \\ \text { Adj. R Square } & 0.726 \\ \text { Std. Error } & 5.195 \\ \text { Observations } & 50 \end{array}

ANOVA
df SS  MS F Signiff  Regression 3605.7736901.44340.0001 Residual 1214.226426.9828 Total 494820.0000 Coeff  StdError t Stat p value  Intercept 1.63355.80780.2810.7798 Income 0.44850.11373.95450.0003 Size 4.26150.80625.2860.0001 School 0.65170.43191.5090.1383\begin{array} { l l l l l l } & d f & \text { SS } & \text { MS } & F & \text { Signiff } \\ \text { Regression } & & 3605.7736 & 901.4434 & & 0.0001 \\ \text { Residual } & & 1214.2264 & 26.9828 & & \\ \text { Total } & 49 & 4820.0000 & & & \\ & & & & & \\ & \text { Coeff } & \text { StdError } & t \text { Stat } & p \text { value } & \\ \text { Intercept } & - 1.6335 & 5.8078 & - 0.281 & 0.7798 & \\ \text { Income } & 0.4485 & 0.1137 & 3.9545 & 0.0003 & \\ \text { Size } & 4.2615 & 0.8062 & 5.286 & 0.0001 & \\ \text { School } & - 0.6517 & 0.4319 & - 1.509 & 0.1383 & \end{array} Note: Adj. R Square = Adjusted R Square; Std. Error = Standard Error
-Referring to Instruction 13.16,when the builder used a simple linear regression model with house size (House) as the dependent variable and education (School) as the independent variable,he obtained an r2 value of 23.0%.What additional percentage of the total variation in house size has been explained by including family size and income in the multiple regression?


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