For each of the regression equations below, calculate the predicted score ( \(Y^{\prime}\) ) for the given scores for \(X_{1}\) and \(X_{2}\).

a. \(Y^{\prime}=1.25+.54\left(X_{1}\right)+.44\left(X_{2}\right) ; X_{1}=2, X_{2}=4\)

b. \(Y^{\prime}=13.82+1.27\left(X_{1}\right)+.13\left(X_{2}\right) ; X_{1}=10, X_{2}=17\)

c. \(Y^{\prime}=88.80+.11\left(X_{1}\right)+.73\left(X_{2}\right) ; X_{1}=145, X_{2}=82\)

d. \(Y^{\prime}=37.09+-.30\left(X_{1}\right)+.25\left(X_{2}\right) ; X_{1}=25, X_{2}=43\)

e. \(Y^{\prime}=4.64+.63\left(X_{1}\right)+-.19\left(X_{2}\right) ; X_{1}=4, X_{2}=18\)