The accompanying table provides data for tar, nicotine, and carbon monoxide (CO) contents in a certain brand of cigarette. Find the best regression equation for predicting the amount of nicotine in a cigarette. Why is it best? Is the best regression equation a good regression equation for predicting the nicotinecontent? Why or why not?

TAR	NICOTINE	CO
6	0.4	5
15	1.0	18
16	1.3	16
13	0.7	18
13	0.8	18
13	0.9	14
16	1.0	17
16	1.2	15
16	1.1	15
9	0.8	12
14	0.7	18
14	0.8	17
13	0.8	18
15	1.0	16
2	0.3	3
16	1.2	18
15	1.1	15
13	0.8	17
15	0.9	15
16	0.9	18
16	1.1	14
14	1.2	15
6	0.5	7
17	1.3	16
15	1.2	13

1. Find the best regression equation for predicting the amount of nicotine in a cigarette. Use predictor variables of tarand/or carbon monoxide (CO). Select the correct choice and fill in the answer boxes to complete your choice. (Round to three decimal places as needed.)

A. Nicotine = ____ + (____) CO

B. Nicotine = ____ + (____) Tar

C. Nicotine = ____ + (____) Tar + (____) CO

2. Why is this equation best?

A. It is the best equation of the three because it has the lowest adjusted R2, the highest P-value, and only a single predictor variable.

B. It is the best equation of the three because it has the highest adjusted R2 the lowest P-value, and only a single predictor variable.

C. It is the best equation of the three because it has the lowest adjusted R2, the highest P-value, and removing either predictor noticeably decreases the quality of the model.

D. It is the best equation of the three because it has the highest adjusted R2, the lowest P-value, and removing either predictor noticeably decreases the quality of the model.

3. Is the best regression equation a good regression equation for predicting the nicotine content? Why or whynot?

A. No, the large P-value indicates that the model is not a good fitting model and predictions using the regression equation are unlikely to be accurate.

B. Yes, the small P-value indicates that the model is a good fitting model and predictions using the regression equation are likely to be accurate.

C. No, the small P-value indicates that the model is not a good fitting model and predictions using the regression equation are unlikely to be accurate.

D. Yes, the large P-value indicates that the model is a good fitting model and predictions using the regression equation are likely to be accurate.