Although a large number of tasks in the computer industry are robotic, a number of operations require human workers. Some jobs require a great deal of dexterity to properly position components into place. A large North American computer maker routinely tests applicants for these jobs by giving a dexterity test that involves a number of intricate finger and hand movements. The tests are scored on a 100-point scale. Only those who have scored above 70 are hired. To determine whether the tests are valid predictors of job performance, the personnel manager drew a random sample of 45 workers who were hired 2 months ago. He recorded their test scores and the percentage of nondefective computers they produced in the last week. These data are stored in columns 1 and 2, respectively, in the file. Can the manager infer at the 05% significance level that the test is a valid predictor? That is, can he infer that higher test results are associated with higher percentages of nondefective units?

Datafile:

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The human resource manager of a telemarketing firm is concerned about the rapid turnover of the firm's telemarketers. It appears that many telemarketers do not work very long before quitting. There may be a number of reasons, including relatively low pay, personal unsuitability for the work, and the low probability of advancement. Because of the high cost of hiring and training new workers, the manager decided to examine the factors that influence workers to quit. He reviewed the work history of a random sample of 80 workers who quit in the last year and recorded the number of weeks on the job before quitting and the age of each worker when originally hired. There data are stored in file HW-6_AgeJob.sav (column 1 contains the work period and column 2 contains the age).

• Use a regression analysis to describe how the work period and age are related.
• Briefly discuss what the coefficients tell you.

Datafile:

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