Statistical Analysis of Employee Bonus Eligibility: Z-Scores and Performance Metrics

This paper analyzes employee bonus eligibility using statistical methods.

Mia Martinez
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Statistical Analysis of Employee Bonus Eligibility: Z-Scores and Performance Metrics
Challenge #2
A lawsuit has been filed against your company by a disgruntled employee. It seems that the bonuses you
awarded were flawed and those who were awarded bonuses based on their high transactions only did because
they ignored a large percentage of customers who would not have purchased anything. Per the company policy,
all customers are to be treated equally. The employees allegedly ignored customers based on gender, ethnicity
and age. You cannot afford a lawyer so you are defending yourself in court and based on your knowledge of
Statistics, you are going to show the judge that your employees were awarded bonuses correctly.
The court wants to review employees with transactions from 80-99. I believe there are six employees in this
category. Please complete the chart below. You must convert each employee’s transaction score and OppVol
into a z-score. You then must identify the area (%) that corresponds to the z-score.
Employee
Number
Employee
Name Transaction z-score OppVol z-score
1
2
3
4
5
6
For Transaction, use the mean 60.76 and the standard deviation 15.11.
For OppVol, use the mean 385.68 and the standard deviation 380.75.
To make the decision below, the employee must be above 70% of their peers in transactions and over 38% in
OppVol. If they exceed both metrics, then the employee does not deserve the bonus.
Solution:
Below is the snapshot of the table, which I prepared in the excel to proof my findings:
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Subject
Statistics

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