1. Consider the CTI-graduates problem. The Dean would like to estimate
   the proportion of CTI-2003 graduates that were offered positions by
   IT consulting firms. 

   a) For a random sample of thirty-six graduates, twenty-four were offered 
      positions by IT consulting firms. Construct and interpret an 80%
      confidence interval for the population proportion.   
   b) Determine the minimum sample size required if the Dean requires
      a level of accuracy of 0.03 with 99% confidence.

2. Consider the data quality problem. The CFO at a local financial
   institution circulates a data quality memo to several senior managers 
   that argues that half of the data (i.e. tuples) in the organizations 
   central database is incorrect. The CIO responds with a memo that
   acknowledges data quality problems, but argues that data quality is
   much better than the CFO contends. As evidence, he cites a recently
   conducted experiment where 45 of 75 randomly selected tuples from the
   database were found to be free of errors. Given these details,
   conduct a test of hypotheses.

3. A colleague is interested in the performance of workstations based
   on the latest Intel CPU architecture. In particular, your colleague 
   is interested in the relationship between CPU clock speed and
   benchmark performance.
   Your colleague decides to investigate and chooses the TOH benchmark
   for her experiment. She tests 25 workstations from different 
   manufacturers and obtains the following statistics:

     Clock Speed: Mean=950Mhz; Std Dev=50Mhz 
     TOH Benchmark score: Mean=100; Std Dev=30
     Pearson correlation between Clock Speed and Benchmark is -0.8

   Note: TOH Benchmark is the time (ms) required to make 25 TOH moves.

   a) Interpret the correlation coefficient.
   b) Assuming that simple linear regression is appropriate: 
      i) Derive the equation of the regression line that may be used to 
         predict TOH Benchmark score from Clock Speed.
         Hint: Let TOH Benchmark be your y variable.
     ii) Interpret the coefficients of the regression equation.