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As a manager, an important function to measure performance is to complete a data analysis comparing scores or metrics. While technology makes it possible to easily acquire data, only you can truly understand what it means; and only choosing one or two data points may not show you an accurate picture of what’s happening. Part of your job as an HR manager is to monitor the performance of trainees as they complete a 4-week paid training program, which includes a product knowledge test. You have to determine which trainees can complete the program, which may require remediation (additional training and re-testing), and which should not continue with the training (termination) based on their scores on the product knowledge exam. Review the mean, standard deviation, and 5-number summary of the trainees’ exam scores below. Mean: 75.5
Standard Deviation: 19.57
Minimum: 18
Quartile 1: 67.75
Median: 80.5
Quartile 3: 87
Maximum: 99
Respond to the following:
Would you prefer to use the mean or the median in this dataset’s measure of central tendency? Why? Based on this training class’s scores, what scores do you think should be considered for completion, remediation, and termination? How did you come to that conclusion?
Do you think that these scores should be the threshold for all training classes? Why or why not?
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