The data below are on the length and weight of 12 American black bears. Suppose the objective is to develop a linear regression model that could be used to predict a bear's weight.

Length (cm) Weight (Kg)

139.0 110

138.0 60

139.0 90

120.5 60

149.0 85

141.0 95

150.0 85

166.0 155

151.5 140

129.5 105

150.0 110

-Determine the correlation coefficient between weight and length.

-Compute the coefficient of determination and comment on the adequacy of the linear regression.

-Find the slope of the regression line.

-Find the y - intercept of the regression line.

-Write the least-squares regression line considering appropriate independent and dependent variables.

-Suppose a 149.50 cm bear is captured in the field. Use the least-squares regression line to predict the weight of the bear.

-Also compute the residual in (h) above if the actual weight is observed as 110 Kg.

-Compute predicted values y and residuals for each set of data (length,weight)

-Plot residuals.