Question

Bivariate data obtained for the paired variables x and y are shown below, in the table labelled Sample data. These data are 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-23733-0.81 In the Calculations table are calculations involving the observed y values, the mean y of these values, and the values y predicted from the regression equation Sample data Calculations 107.7 155.1 117.3 135.2 127.8 139.8 138.3 116.6 151.1 120.0 25.0700 280.6630 473.4976 50.6517 35.8561 75.8118 64.5291 280.2276.20 25.6137338.5968 177.9556 140 80.5865 3.4596 0.2228 41.73 16130 110 213.0035 764.5982 976.8720 sums 10 120 130 140 150160 Send data Jto Excel Figure 1 Answer the following:
Answer the following: 1. The total variation in the sample y values is given by the 2 which for these data is 2. The value r is the proportion of the total variation in the sample y values that is explained by the estimated linear relationship between x and y. For these data, the value of r is (Round your answer to at least 2 decimal places.) 3. For the data point (117.3, 135.2), the value of the residual is . (Round your answer to at least 2 decimal places.) 4. The least-squares regression line given above is said to be a line which best fits the sample data. The term best fits is used because the line has an equation that minimizes the which for these data is?
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Answer #1

1)total variation is given by SSy =\sum(y-\overline{y})2 which for this data is 976.8720

2) the value of r2 is =764.5982/ 976.8720=0.78

3)

residual =actual-predicted= 135.2-(237.33-117.3*0.81)=-7.12

4)

that minimizes the sum of square of error SSE =\sum(y-\widehat{y})2   which for this data is 213.0035

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