2 Part week 2 DAT/565
The most frequently used measures of central tendency for quantitative data are the mean and the median. The following table shows civil service examination scores from 24 applicants to law enforcement jobs:
83 74 85 79
82 67 78 70
18 93 64 27
93 98 82 78
68 82 83 99
96 62 93 58
Using Excel, find the mean, standard deviation, and 5-number summary of this sample.
- Construct and paste a box plot depicting the 5-number summary.
- Does the dataset have outliers? If so, which one(s)?
- Would you prefer to use the mean or the medianas this dataset’s measure of central tendency? Why?
Due Day 7
Reply to at least 2 of your classmates or your faculty member. Be constructive and professional.
In the data showed below, it has 18 and 27 as outliers. Considering these are exam scores, these outliers are pretty low. There may need to be some investigation on why these two scores were so far below the average. Since we have these outliers, I’d use median. The strong outliers skew the overall scores. The median gives us a higher average score that might be closer to the truth. If I wanted to intelligently guess how the average person would perform, the median would take away the fluke low scores.
I could use this system to monitor the necessity to update or change the test. If it were too easy or hard, I’d know which direction to adjust training. I could also use the scores to measure the capacity of the qualified candidates against other candidates that test in other fields.
Later, I might compare employees test scores to there overall performance relative to good or poor behavior. I would look for any correlations. Low passing scores may indicate higher risk of not following policies. This could increase risk in other areas like civil suites, bad media, and civil suit payouts which all increase expenses.
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An outlier is an extreme value that is far enough from the majority of the data that it probably arose from a different cause or is due to measure error. According to the site, Whatis.com, an outlier is a single data point that gives far outside the average volume of a group of statistics. Furthermore, outliers maybe exceptions that stand outside individual samples of populations. In simpler terms an outlier is an individual that is markedly different from the norm. Outliers are an important factor in statistics because they impact the overall results, which in turn can dramatically affect averages and potentially skew the results of any study. In relation to our exercise this week, I would say that there are outliers and it aligns with the symmetrical graph .