2. A high-sensitivity 32P marker analysis was used to determine a certain DNA adduct content (per 108 nucleotides) in the lung tissue of 12 patients with lung cancer.

Their smoking amount (cigarettes/day) was also investigated. The data are given in Table 13.4.

(a) Draw a scatterplot and visually explore the relationship between smoking amount and DNA adduct content. Judge whether it is appropriate to fit a simple linear regression for these data.

(b) Perform a regression analysis and interpret the results you obtained.

(c) Check whether the underlying assumptions of linear regression was violated using a residual plot.

(d) Calculate and explain the meaning of coefficient of determination in this case.

(e) Based on the regression equation you obtained in (b), predict the lung tissue DNA adduct content for patients who smoke 10 cigarettes per day. Calculate the 95% CI and 95% prediction interval and explain their implications and difference.

(f) Is it appropriate to predict the lung tissue DNA adduct content for patients smoking 40 cigarettes per day using the regression equation? Explain the reason.
(g) How do you identify outliers? What impact might they have? What will you do about them?