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

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 calculates square of deviations of the points from the line chosen using Linear Regression. Our target is that this error should be

The least squares regression line minimizes the sum of the _____Group of answer choicessquared differences between actual and predicted y valuesabsolute deviations between actual and predicted x valuesdifferences between actual and predicted y valuesabsolute deviations between actual and predicted y values

42.In practice, the line of best fit or regression line is found when:  A. Sum of the square of residuals ( ? (Y-h(X))2) is minimum  B. Sum of residuals (?(Y – h(X))) is minimum  C. Sum of the absolute value of residuals (?|Y-h(X)|) is maximum  D. Sum of the square of residuals ( ? (Y-h(X))2) is maximum

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