like	moisture	sweetness
64	4	2
73	4	4
61	4	2
76	4	4
72	6	2
80	6	4
71	6	2
83	6	4
83	8	2
89	8	4
86	8	2
93	8	4
88	10	2
95	10	4
94	10	2
100	10	4

1. Using R programming from the above brand dataset, depict a Type II sum of squares ANOVA table for a regression of liking (Y ) on moisture (X1) and sweetness (X2).

2. From the above ANOVA table, state the hypotheses being tested in each row, along with the full and reduced models in each row.

3. ) From the above ANOVA table, what are each of these quantities:

SSR(X1|X2)

SSR(X2|X1)

SSE(X1, X2)

4. Using the above ANOVA table, demonstrate how to obtain the first row's value of F manually from the sums of squares and the degrees of freedom.

5. Is it possible to run an F-test lack-of-fit for these data? Why or why not? If so, run one where we are testing the lack-of-fit of the model: Yi = 0 + 1Xi1 + 2Xi2 + i. State your conclusions.

6. Run an overall F-test of the model: Yi = 0 + 1Xi1 + 2Xi2 + i. State your hypotheses, and state your conclusions

7. Describe in words what the difference is between the lack-of-fit test and the overall F-test.