Use the results from Problem 4 in Chapter 8, as well as the computer output given here, to answer the following questions about the data from that problem.
a. Conduct the overall regression F test for the model where Y is regressed on X1, X2, and X3. Use α = .05. Interpret your result.
b. Provide variables-added-in-order tests for the order X2, X1, and X3.

c. Provide variables-added-in-order tests for the order X3, X1 and X2.
d. List all orders that can be tested, using the computer results below and in Problem 4 of Chapter 8. List all orders that cannot be so computed.
e. Provide variables-added-last tests for X1, X2, and X3.
f. Provide the variables-added-last test for X4 = X2X3 given that X2 and X3 are already in the model. Does X4 significantly improve the prediction of Y given that X2 and X3 are already in the model?

Y Regressed on X2 and X1 F Value Pr> F Source DF X2 X1 Type I SS Mean Square 308.339479 9.458932 1308 33947941.390001 9.458932 .300.5915 Mean Square F Value Pr>F SourceDF X2 X1 Type III sS 1309 445931 9.458932 41.42 5,0001 0.30 0.5915 1309.445931 9 458932 Y Regressed on X3 and X1 Source DF Type I sS Mean Square F Value Pr> F 387 599718 35.632307 1387 599718 541 0001 1.40 0.2526 X3 X1 35.632307 Source DF Type Ill SSMean Square F Value X3 X1 Pr> F 55.68 .0001 136.83230735 652307140 02528 1414.879544 1414.879544 35.632307 Regressed on X3 and X2 Source DF Type I ss Mean Square F Value Pr> F x3 1387.599718 1387,599718 64 22 0001 464 0459 X2 100.259687 100 259687 Source DF Type III SS Mean Square F Value Pr> F X3 X2 179.5199260 8.31 100 2596869 100.2596869 4.64 179.5199260 0.0103 0.0459 100 2596869 Y Regressed on X1, X2, and X Type I SS Mean Square F Value Pr>F Source DF X1 X2 X3 8.352481 1309 445931 200 340530 8.352481 1309 445931 200.346b30 0.40 0.5378 62.16 < 0001 9.51 0.0071 Source F Type Il SS X1 X2 X3 30.2855361 94 9129162 1200.3465296 Mear Square | F Valu | Pr > F 144 0.2480 451 0.0497 951 0.0071 30.2855361 4 9129162 200.3465296