PERT Survey Research conducted quantitative surveys in an effort to measure the effectiveness of

various campaigns. Suppose on their survey instrument, they used a continuous scale of from 0 to 10

where 0 denotes that the campaign is not effective at all, 10 denotes that the campaign is extremely

effective, and other values fall in between to measure the effectiveness. Suppose also that a particular

campaign received an average of 3.6 on the scale with a standard deviation of 1.4 early in the tests. Later,

after the campaign had been critiqued and improved, a survey of 35 people was taken and a sample

mean of 4.0 was recorded. What is the probability of this sample mean or one greater occurring if the

actual population mean is still just 3.6? Based on this probability, do you think that a sample mean of 4.0

is just a chance fluctuation on the 3.6 population mean, or do you think that perhaps it indicates the

population mean is now greater than 3.6? Support your conclusion. Suppose a sample mean of 5.0 is

attained. What is the likelihood of this result occurring by chance when the population mean is 3.6?

Suppose this higher mean value actually occurs after the campaign has been improved. What does it

indicate?