hmw6

Instructions: Complete each problem on a separate worksheet in a single Excel file. Rename the separate worksheets with the respective problem number. You may have to copy and paste the datasets into your homework file first. Name the file with your last name, first initial, and HW #6. Label each part of the question. When calculating statistics, label your outputs. Submit your completed file in Blackboard.

1. The director of a university’s career development center is interested in comparing the starting salaries of male and female students who recently graduated from the university and commenced full-time employment. The director has formed pairs of male and female graduates with the same major and similar grade-point averages. Specifically, she has collected a random sample of 50 such pairs and has recorded the starting salary of each person. In the file 310homework6data.xlsx, problem #1 data contains the salary information collected. Calculate a 95% confidence interval for the mean difference between similar male and female graduates of the university. Interpret your results.

2. The manager of an employment agency wants to be able to better match up new employees with contractors looking to hire people with computer experience. She collects a random survey of 82 employees and asks them background questions she thinks might impact their computer proficiency. The data is in the file 310homework6data.xlsx in Problem #2.

a. Sort the data by gender and calculate the mean and standard deviation of computer experience for each gender. Use that information to construct a 95% confidence interval for the difference in the two means. Interpret the result.

b. Sort the data by whether or not the employee owns a PC at home. Perform the same calculation as above and interpret the results of the confidence interval.

c. Which categorical variable seems to be a better predictor for PC knowledge? Gender or PC ownership?

3. A producer of steel cables wants to know whether the steel cables it produces have an average breaking strength of 5000 pounds. An average breaking strength of 5000 pounds would be inadequate, and to produce steel cables with an average breaking strength of more than 5000 pounds would unnecessarily increase production costs. The producer collects a random sample of 64 steel cable pieces. The breaking strength for each is recorded.

a. Identify the null and alternative hypothesis for this situation.

b. What would be the meaning of a Type I error in this context?

c. What would be the meaning of a Type II error in this context?