Breast cancer mortality data:
The data contain breast cancer mortality (y) from 1950 to 1960 and the adult white female populations (x) in 1960 for 301 counties in North Carolina, South Carolina, and Georgia.

1.  Access the data:
a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/cancer.txt", header=TRUE)

2.  Construct a scatterplot of y on x.
3.  Run the regression through the origin of y on x.
4.  Check the assumptions.
5.  Now run the regression of y on sqrt(x).
6.  Check the assumption of the model of question 5.


Asbestos fibers data:
1.  Read the paper (see link on the course website).
2.  Summarize the paper in less than one page.
3.  Access the data:
a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics13/asbestos.txt", header=TRUE)

Study the relationship between the two measurements.  Treat the more accurate measurements (SEM) as the predictor and the PCM measurements as the response variable.