RE: W3_A1_ How should this question be answered? The question I answered from the sight this is what the Professor has asked. I need the help by 2:00 on Monday May 22, 2017. Can you help/ I like how...

RE: W3_A1_

How should this question be answered? The question I answered from the sight this is what the Professor has asked. I need the help by 2:00 on Monday May 22, 2017. Can you help/

I like how you arrived at the exact raw score that would cut off the top 25% of applicants. However, I would argue that we don't need to go back to raw scores to identify those in the top 25%. Once we know the z-score of 0.67 cuts off the top 25%, we also know that any applicant with a z-score of 0.67 or greater would be in the top 25%.

I agree that z-scores allow us to determine how one score relates to all other scores in a distribution. I would also add that in order to compute z-scores we need to know the mean and the standard deviation for the distribution of scores. In addition, one of the most useful aspects of using z-scores is comparing the relative performance of two raw scores. Let's say you worked for a company that wanted to know which of two employees was better; an employee in New York or an employee in California. By computing z-scores for each employee the company can better compare which employee is performing better. But why wouldn't simply comparing raw customers service scores for each employee be better in order to determine which employee performed better? In other words, why do z-scores give us a more accurate comparison in order to determine "better" performance?