# Question

Refer to Exercise 12.23. Fit a complete second- order model relating y to x1, x2, x3, and x4. That is, include both first- and second- order terms in the four variables along with all six cross-product terms, xi xj.

a. Compare the R2 values for the three models. Which model appears to provide the best fit?

b. Test at the .05 level whether any of the cross- product terms provide a significant relationship with y, maximal oxygen uptake.

c. Which of the three models would you recommend? Justify your answer.

a. Compare the R2 values for the three models. Which model appears to provide the best fit?

b. Test at the .05 level whether any of the cross- product terms provide a significant relationship with y, maximal oxygen uptake.

c. Which of the three models would you recommend? Justify your answer.

## Answer to relevant Questions

Refer to the feed efficiency data in Exercise 12.14. The researcher is relating y, feed efficiency, to the explanatory variables: x1, amount of feed additive; and x2, amount of copper placed in the feed. Consider the ...Refer to Exercise 12.2. a. Write a second- order general linear model that allows for different slopes and intercepts for each mode of drive mechanism. b. Display the second- order regression equation for each of the three ...Refer Exercise 12.35 Fit a single model to the data that will relate x, the soil mercury content. To y, the plant mercury contents, with separate intercepts and slopes for the three crops. a. Does there appear to be a ...Suppose that we have 10 observations on the response variable, y, and two explanatory variables, x1 and x2, which are given below in matrix form. a. Compute X’ X, (X’ X)-1, and X’ Y, b. Compute the least-square ...A chain of small convenience food stores performs a regression analysis to explain variation in sales volume among 16 stores. The variables in the study are as follows: Sales: Average daily sales volume of a store in ...Post your question

0