STAT 516 HW 2 

Please write your answers neatly and clearly!

You MUST make sure your answers to these questions are
written in the same order as the questions are listed in 
the assignment.  If this instruction is not followed, 
your homework WILL NOT be graded.

HAND CALCULATIONS:

1.  We will analyze the data in Table 7.14 on pg. 327 of the textbook.  
The dependent (Y) variable is Sugar (sugar content of a fruit) and the 
independent (X) variable is Days (number of days after picking it).

Do the following by hand, SHOWING WORK.  You may use SAS to check your answers 
if you want.

Use the answers from Problem 1 of HW 1 to help answer these questions:

(a)  Find the correlation coefficient r.  What does this tell you about the 
nature of the relationship between sugar and number of days?  Be specific!

(b)  Find the residual for the second observation in the data set.

(c)  Find a 95% prediction interval for the sugar content of a new fruit 
which was picked after 2 days.

COMPUTER CALCULATIONS:

2.  Look at the data in Table 5.1 on page 186 of the textbook. 
We will analyze only the observations having "Big8 = YES".

This modified data set is also given in the SAS code "auditdata.txt" on the 
course web page. (Equivalent R code to read in the data is given as 
"auditdataR.txt" on the course web page.)

The dependent variable is fee (audit fees charged) and the independent 
variable is pop (population) for a sample of 13 cities using Big 8 firms.

The fee variable is measured in THOUSANDS of dollars, and the population 
variable is measured in THOUSANDS of people.

(a)  Using SAS or R, find a 95% confidence interval for the mean audit fees 
for all cities having population 100 thousand people.  Also, 
find a 95% prediction interval for the audit fees for a new city having 
population 100 thousand people.

(b)  Using SAS or R, make a residual plot and Q-Q plot of the residuals for this 
regression.  Comment about whether each of the regression assumptions seems 
to be violated, based on the plots.

(c)  Find the r^2 for this regression from the SAS or R output, and interpret it 
in the context of this data set.


TRUE-FALSE QUESTIONS:

3.  Answer True/False Concept Questions 2,13,14,17,19,20 
on pages 326-327.  If the statement is false, either correct it or explain 
why it is false.  If you only write "FALSE", that is NOT sufficient.