Pct.BF Age Waist Thigh Bicep Wrist 14.9 56 35.19685 58.4 34.6 18.8 5.2 55 32.598425 54.4 29.4 17 16 47 33.897638 58.1 30

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Pct Bf Age Waist Thigh Bicep Wrist 14 9 56 35 19685 58 4 34 6 18 8 5 2 55 32 598425 54 4 29 4 17 16 47 33 897638 58 1 30 1 (70.72 KiB) Viewed 153 times

Pct Bf Age Waist Thigh Bicep Wrist 14 9 56 35 19685 58 4 34 6 18 8 5 2 55 32 598425 54 4 29 4 17 16 47 33 897638 58 1 30 2 (55.87 KiB) Viewed 153 times

Pct.BF Age Waist Thigh Bicep Wrist 14.9 56 35.19685 58.4 34.6 18.8 5.2 55 32.598425 54.4 29.4 17 16 47 33.897638 58.1 30.6 17.6 12.2 43 35.11811 60.2 31.7 18.6 15.2 28 38.897638 63.4 33 19.9 16.7 40 34.094488 55.9 29.8 17.3 10.1 27 28.661417 53.6 27.8 17.4 25.4 43 38.818898 59.5 30.1 17.7 10.9 55 37.519685 57.4 34.1 19.2 8 51 32.283465 49.3 29.6 16.9 18.7 50 38.425197 60 32.7 19 16 28 35.275591 64.2 37.2 18.5 21.4 40 36.338583 57.5 32.1 17.3 26.1 62 41.259843 61.6 36.2 20.2 15.6 31 30.07874 57.4 27.9 16.7 19.2 26 35.708661 58.4 31.9 17.7 9.6 38 36.062992 60.6 31.6 18.5 4 47 27.716535 50.6 26.8 16.8 10.6 57 34.015748 53 31.7 16.9 19.2 35 37.440945 64.8 36.4 19.4 12.3 23 33.543307 59 32 17.1 27 70 37.362205 56 31.2 19.2 16.9 36 35.551181 59.2 32.4 17.8 14.9 72 34.685039 57.2 32.6 18.8 12.4 54 36.141732 57.7 31.4 18.9
Unless otherwise stated, carry out inferences using a = 0.05. Hypotheses should be written in terms of parameters when possible, and conclusions of hypothesis tests should be given using the context of the problem. Obesity researchers randomly selected 50 male patients to a local clinic, and obtained permission to access their medical records; the data appear in a file called bodyfat21.txt. The continuous variables in the data set are the subjects' percent body fat, their age (years), waist size (inches), thigh circumference (cm), bicep circumference (cm), and wrist circumference (cm). a) Use Minitab to obtain a model chosen by backward selection, using Qout = 0.05. Provide the estimated regression function, the coefficients table, and a table of output detailing the actions taken at each step in the automated procedure. Write a summary statement describing what happened at each step of the process. b) Compare the final models chosen by the two automated selection procedures, and explain whether you are surprised by the results. c) Use the best subsets approach to consider a collection of first-order models. i. Provide concise output representing the "best" models, restricted to p = 3. ii. Which is the best model (p = 3) if R&. is used as the selection criterion? iii. Would the same model be chosen if AIC, were the criterion? iv. Would the same model be chosen if PRESS, were the criterion?