The variation in the sample y values that is explained by the estimated linear r

Question

The variation in the sample y values that is explained by the estimated linear relationship between x and y is given by the, which for these data is The value r^2 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^2 is. (Round your answer to at least 2 decimal place.) For the data point (4.8, 1.1), the value of the residual is. Round your answer to at least 2 decimal places.) 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

Explanation / Answer

From given tables we have

SSR=Regression sum of square =10.9644

SSE=Sum of squares due to error =0.8387

SST=total sum of square =11.8880

So, R2=10.9644/11.8880=0.92230821

Part-1

Coefficient of determination which for these data is 0.92230821

Part-2

0.92

Part-3

Equation is Y=5.871521456-1.094278283 *X

So predicted Yhat=5.871521456 -1.094278283*4.8=0.618985698

Hence residual =actual-yhat=1.1-0.62=0.48

Part-4 is correct

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