A simple regression model has this partial ANOVA table source sum of squares degrees of freedom regression 9,838.9 3 error 1,126.8 32 What is R^2, the coefficient of determination?
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9 + 1126.8 Total Sum of Squares = 10965.7 ** Show more…
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Below you are given a partial computer output based on a sample of 16 observations. Coefficient Standard Error Constant 12.924 4.425 X1 -3.682 2.630 X2 45.216 12.560 ANOVA Source of Variation Degrees of Freedom Sum of Squares Mean Square F Regression 4,853 2,426.5 Error 485.3 Based on partial data, the "unadjusted" R-square for the model would be approximately . . .
Adi S.
Calculate and interpret the Coefficient of "determination" (r2) and the Coefficient of non-determination (1-r2) (Use the information in the box below and/or use your own calculation:) Regression Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .728a .530 .530 15.289 a. Predictors: (Constant), Homework Grade
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The following problem is reprinted from the November 1989 Actuarial Examination on Applied Statistical Methods. Source: Society of Actuaries. You are given $$\begin{array}{|c|c|c|c|c|}\hline X & {6.8} & {7.0} & {7.1} & {7.2} & {7.4} \\ \hline Y & {0.8} & {1.2} & {0.9} & {0.9} & {1.5} \\ \hline\end{array}$$ Determine $r^{2}$ , the coefficient of determination for the regression of$Y$ on $X .$ Choose one of the following. (Note: The coefficient of determination is defined as the square of the correlation coefficient.) $\begin{array}{llllll}{\text { (a) } 0.3} & {\text { (b) } 0.4} & {\text { (c) } 0.5} & {\text { (d) } 0.6} & {\text { (e) } 0.7}\end{array}$
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