Hypothesis testing can be important when developing performance standards for

your subordinates. Each of you will be a manager, and each of you will

therefore need to develop performance standards which will clearly allow you

(and your subordinate) to agree as to whether or not the subordinate met your

requirement. You do not want to end a rating period with disagreement on the

subordinate’s performance, and you do not want to lose a grievance to upper

management should the subordinate appeal your performance rating. (A

subordinate certainly has every right to appeal, but you should never lose an

appeal!)

Suppose that you are manager of a restaurant, and need to develop a series of

performance standards for each member of your staff. The restaurant is a

full-service restaurant, with seated customers, menus, a hostess to meet

customers and seat customers, etc. Examples might include Joe Theismann’s,

an IHOP, an Outback Steakhouse, etc.

For this case study, develop one measurable, numeric performance standard for

a member of the wait staff. Then show how you could take a random sample of

30 readings of the performance and develop a hypothesis test using the t

statistical method to determine, at 95% confidence, if the performance

standard was met. List 30 notional (hypothetical) “readings” and calculate

a corresponding notional t-test to show how your subordinate hypothetically

performed. You will need to calculate the sample mean, sample standard

deviation, use the t table in the back of the book, etc., to complete the

analytics. You must use Excel to log your data and perform many or all of

your analytics, and you will submit your Excel file (and any other files you

may find convenient to submit such as photos of your calculations if done

long-hand). This may be a one-tail test.

At the 95% confidence level, using the notional data, can you conclude that

the subordinate is meeting your standard

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