Refer to the data of Exercise 12.13. The experiment was also concerned with the effects of high…
Refer to the data of Exercise 12.13. The experiment was also concerned with the effects of high levels of copper in the chick feed. Five of the 10 chicks in each level of the feed additive received 400 ppm of copper, while the remaining five chicks received no copper. The data are given here.
Let y be the feed efficiency ratio, 1 be the amount of the feed additive, and 2 be the amount of copper placed in the feed. Fit the following two models:
a. Which of the two models appears to provide the better fit to the data? Justify your answer.
b. Display the predicted equation for the best-fitting model.
c. Explain the meaning of 1 in the best-fitting model.
A poultry scientist was studying various dietary additives to increase the rate at which chickens gain weight. One of the potential additives was studied by creating a new diet that consisted of a standard basal diet supplemented with varying amounts of the additive (0, 20, 40, 60, 80, and 100 grams). There were 60 chicks available for the study. Each of the six diets was randomly assigned to 10 chicks. At the end of 4 weeks, the feed efficiency ratio, feed consumed (gm) to weight gain (gm), was obtained for the 60 chicks. The data are given here.
a. In order to explore the relationship between feed efficiency ratio (FER) and feed additive (A), plot the mean FER versus A.
b. What type of regression appears most appropriate?
c. Fit first-order, quadratic, and cubic regression models to the data. Which regression equation provides the best fit to the data? Explain your answer.
d. Is there anything peculiar about any of the data values? Provide an explanation of what may have happened.