Question: Ten adults completed a six-week smoking cessation program. The program coordinator suspected that the number of years a person smoked before entering the program was associated with the number of days that they remained smoke-free in the year after starting the smoking cessation program. (5 points)

1. What is the independent variable? (¼ pt)
2. What is the dependent variable? (¼ pt)
3. What type of data is the dependent variable? (¼ pt)
4. What is the mean number of days the participants remained smoke-free since entering the program? (¼ pt)
5. Using simple, linear regression for this data, what is the formula of the line that best fits these data? (½ pt)
6. Is the slope of this regression line statistically significant? What does it mean when the slope is statistically significant? (½ pt)
7. How many days would you expect a 15-year smoker to remain smoke-free after the smoking cessation program? (½ pt)
8. What percentage of the variance of number of days remaining smoke-free is explained by knowing the number of years smoked before the intervention? What percentage of the variance cannot be explained? (½ pt)
9. What other factors could account for the variance that is not explained by knowing the number of years smoked? (½ pt)
10. What percentage of the variance of number of days remaining smoke-free is explained by knowing the number of years smoked before the intervention if the program only included smokers who have smoked more than the past five years? (½ pt)
11. Why are the answers to h and j different? (½ pt)
12. What is the correlation coefficient for the original data? What does it mean? (½ pt)

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