Larger values of r ^ 2 that the observations are more closely grouped about the A. origin B. None C. average value of the dependent variable D. least squares line E. average value of the independent variables

nts/routeassignment/be6c3509-917d-11eb-a9aa-06036a82e976 us Next 7. Which equation represents the line of best fit for the scatter plot below? 10 8. 3 2 1+ 1 3 6. 7 A. y = x B. y =x+ 2 С. у %3D х +2 D. у %3D 2

4. A study was conducted to investigate the relationship between the size of a house (in square feet) and the selling price of a house (in dollars). The response variable is price in dollars, and we want to study if the covariate of the square footage helps explain the response. A random sample of 522 houses was used, and the linear regression output from R is below. price sqft, data = house) 1m (formula = Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -81432.946 11551.846 -7.049 5.74e-12 *** sqft 158.950 4.875 32.605 <2e-16 *** Residual standard error: 79120 on 520 degrees of freedom Multiple R-squared: 0.6715, Adjusted R-squared: 0.6709 a. Write out the estimated linear equation. What is the estimated expected selling price of a house that is 2000 square feet? b. Does the intercept have a useful interpretation in this study? Why or why not. c. Interpret the slope estimate in context of the model.

Compute the least-squares regression line for predicting the right foot temperature from the left foot temperature. Round the slope and y-Intercept values to four decimal places.