3.15. Solution concentration. A chemist studied the concentration of a solution (Y) over time (X). Fifteen...

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3.15. Solution concentration. A chemist studied the concentration of a solution (Y) over time (X). Fifteen identical solutions were prepared. The 15 solutions were randomly divided into five sets of three, and the five sets were measured, respectively, after 1, 3, 5, 7, and 9 hours. The results follow. i: 1 2 3 13 14 15 X;: Y;: 9 .07 9 .09 9 1 1 1 .08 2.84 2.57 3.10 a. Fit a linear regression function. b. Perform the F test to determine whether or not there is lack of fit of a linear regression function; use a = .025. State the alternatives, decision rule, and conclusion. c. Does the test in part (b) indicate what regression function is appropriate when it leads to the conclusion that lack of fit of a linear regression function exists? Explain. 3.15. Solution concentration. A chemist studied the concentration of a solution (Y) over time (X). Fifteen identical solutions were prepared. The 15 solutions were randomly divided into five sets of three, and the five sets were measured, respectively, after 1, 3, 5, 7, and 9 hours. The results follow. i: 1 2 3 13 14 15 X;: Y;: 9 .07 9 .09 9 1 1 1 .08 2.84 2.57 3.10 a. Fit a linear regression function. b. Perform the F test to determine whether or not there is lack of fit of a linear regression function; use a = .025. State the alternatives, decision rule, and conclusion. c. Does the test in part (b) indicate what regression function is appropriate when it leads to the conclusion that lack of fit of a linear regression function exists? Explain.

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a Fit a linear regression function The data can be summarized as follows X hours Y solution concentration 1 284 1 257 1 310 3 292 3 282 3 295 5 301 5 ... View the full answer