1) The least squares procedure minimizes the sum of

a)the residuals

b)squared maximum error

c)absolute errors

d)squared residuals

e)none of the above

2)a residual is

a)the difference between the mean of Y conditional on X and the unconditional mean

b)the difference between the regression prediction of Y and its actual value

c)the difference between the sum of squared errors before and after X is used to predict Y

d)the difference between the mean of Y and its actual value