1 Our first example of regression (Example 4.1, page 94) presented data showing that people who increased their nonexerc

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1 Our first example of regression (Example 4.1, page 94) presented data showing that people who increased their nonexercise activity (NEA) when they were deliberately overfed gained less fat than other people. The scatterplot and regression line based on 16 overfed subjects are displayed in Figure 4.1, page 94. Figure 23.11 shows the Minitab output for regressing fat gain on NEA change in this study, along with prediction for a person adding 500 NEA calories. Exercises 23.13 to 23.22 are based on

this information. . Minitab O x Regression Analysis: fatgain versus NEAchange Model Summary s R-59 R-sq(ad) PRESS R-sg(pred) 0.739853 60.614 57.804 9.62306 50.549 Coefficients Term Coet SE Coef 958 CI Constant 3.505 0.304 ( 2.854, 4.156) NEAchange -0.003442 0.000741 (-0.005032, -0.001851) Prediction for fatgain Variable Setting NEA 500 T-Value 11.54 -4.64 P-value VIE 0.000 0.000 1.00 Fit SE Fit 1.78438 0.226039 958 CI 958 PI (1.29957, 2.26919) (0.125146, 3.44361) Figure 23.11 Baldi/Moore, The Practice of Statistics in the Life Sciences, 4e, o 2018 W.H. Freeman and Company FIGURE 23.11 Minitab output for the nonexercise activi- ty (NEA) change and fat gain data, with prediction for x*=500.z* = 500. .

23.16 Is there significant evidence that fat gain decreases as NEA change increases? To answer this question, we test the hypotheses a. HO:B=0H : B = 0 versus Ha:B<0.H. : B<0. b. HO:B=0H: B = 0 versus Ha:3+0.H.: B0. c. HO:a=0 Ho : a =0 versus Ha:a<0.H, : a < 0.

23.18 Which of the intervals in the Minitab output is the 95% confidence interval for the population slope B?s? a. (2.854, 4.156) b. (-0.005032, -0.001851) c. (1.29957, 2.26919) 23.19 The interpretation in context of the 95% confidence interval for the population slope BB is that we are 95% confident that a. fat gain decreases by some amount in this interval for every 1 additional Calorie in- crease in NEA.

b. fat gain decreases, on average, by some amount in this interval for every 1 addition- al Calorie increase in NEA. c. 95% of individuals who increase their NEA by 1 Calorie decrease their fat gain by some amount in this interval.