Question

Geoff Brown is the manager for a telemarketing firm and is evaluating the sales rate of experienced workers in order to set minimum standards for new hires. During the past few weeks, he has recorded the number of successful calls per hour for the staff. These data appear next along with some summary statistics he worked out with a statistical software package. Geoff has been a student at the local community college and has heard of many different kinds of probability distributions (binomial, normal, hypergeometric, Poisson, etc.). Could you give Geoff some advice on which distribution to use to fit these data as well as possible and how to decide when a probationary employee should be accepted as having reached full production status? This is important because it means a pay raise for the employee, and there have been some probationary employees in the past who have quit because of discouragement that they would never meet the standard. Successful sales calls per hour during the week of August 14:

4 2 3 1 4 5 5 2 3 2 2 4 5 2 5 3 3 0 1 3 2 8 4 5 2 2 4 1 5 5 4 5 1 2 4

Descriptive statistics:
N: 35 MEAN: 3.229 MEDIAN: 3.000 STANDARD DEVIATION: 1.682  MIN: 0.0 MAX: 8.0 1ST QUARTILE: 2.0 3RD QUARTILE: 5.0

Analyze the distribution of sales calls. Which distribution do you think Geoff should use for his analysis? Support your recommendation with your analysis. What standard should be used to determine if an employee has reached “full production” status? Explain your recommendation.  

Answer 1