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ID: 3324887 • Letter: H
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hould go to should go to r: 106 hro met Press for rge Hor Hey www-awh.aleks.com Cheps Study 1 Guided Solutiorns and Study H PWORKSHENK REPORT OPTIONS EnlishDaniela Dian ALEKS: Daniela Diaz ALEKS Dictien Calculator Business Stat Bivariate data obtained for the paired variables x and y are shown below, in the table labelled "Sample data. These data atre plotted in the scatter plot in Figure 1, which also displays the least squares regression line for the data. The equation for this line is y=0.68 +0.72 x In the 'Calculations" table are calculations involving the observed y values, the mean y ot these values, and the values predicted from the regression equation. Sample dat 2.8764 0 2663 0.7 1.7 22 16 32 31 41 30 52 50 1 037 0.44091 1.6384 .0484 00144 0 0108 0 5655 2.3839 62161 0.0135 3994 03318 1 4518 5880 Figure 1 Answer the folowing . For the data point (5.2, 5.0, the value of the tesidal is ]. (Round your anower to at least 2 decima places 2 The varation in the sample yvalues that is explained by the estimated linear relationship between x and y is given by the which for these data is 7 . The proportion of the total vanlation in the sample yvalues that can be explained by the estimated linear relationship between x and y is -(Round your anewer to at least 2 decimal places) The least-squares regression ine given above is said to be a lne which best tts" the sample data. The tem "best fts" is used because the line has an equation that miniies the D.which ftor these dats isBExplanation / Answer
1. Here,
the linear regression line
y^ = 0.68 + 0.72x
y^(5.2) = 0.68 + 0.72 * 5.2 = 4.424
Residual = 5.0 - 4.424 = 0.576
Q.2
Regression Sum of squares which is 6.2161
Q.3 Here
R2 = SSW/ SST = 6.2161/ 7.5880 = 0.8192
so 81.92% is explained by the estimated linear relationship between x and y
Q.4
That minimize the the sum of squared vertical distances from observed values or the square error. Which is here 1.4518
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