Intuitively, the best point estimates for the regression parameters β0, β1, ..., βk, are those that ______Multiple choice question.lie on a straight line.minimize the residuals.are small.minimize the predicted values.

In choosing the best fitting line through a set of points in a linear regression, we choose the one with the __________. a. smallest sum of squared residuals b. largest sum of squared residuals c. smallest sum of squared error d. a and c

The method of least squares finds the best fit line that _______ the error between observed & estimated points on the linea.Maximizesb.Minimizesc.Reduces to zerod.Approaches to infinityClear my choice

The method of least squares dictates that we choose a regression line where the sum of the square of deviations of the points from the lie is:*2 pointsMaximumMinimumZeroPositive

The best-fitting line minimizes the residuals.Group of answer choicesTrueFalse

Question 6All of these options are useful error measures to compare regressions except:1 pointSSER squaredTSSROC index