Southern New Hampshire University Data Outliers Discussion

We know that many types of data fall into a normal distribution, with most of the observations falling toward the middle. However, sometimes there are outliers, or data points that are very different (i.e., larger or smaller) from the others in the sample. An example from psychology would be Mensa, which requires 98th percentile on a valid, normed test of intelligence for admission. Mensa members are therefore outliers, although some are more so than others. Review the Slate article on the New England Patriots from the module resources, Another Data Point, for an example of an outlier in the real world. Choose an example of an outlier in the real world and discuss its effect. When responding to your classmates’ posts, evaluate the effects of their chosen outliers.

To complete this assignment, review the Discussion Rubric document (attached).

PLEASE ALSO REPLY TO THE FOLLOWING TWO STUDENTS REGARDING THE SAME RESPONSE:


STUDENT ONE:

The article this week was pretty hard for me to get through because I don’t follow sports. The statistics behind it seem simple enough, I just zone out when I start to hear sports-talk. That being said, I’m sure lots of people are very interesting about the Patriots and their non-fumble streak. I’m sure there is a lot of math and statistics that can go into any sport, I just haven’t really thought about it until now. The conclusion to the article seemed to wrap up the piece nicely, “the Patriots’ sudden improvement in preventing fumbles doesn’t close the case against them,” but the statistic should be used along with other evidence when making a case (Ellenberg, 2015). I like this sentiment as it seems like a nice combination of statistics meets “real world” problems.

The first outliers that comes to my mind is at my work, a research center. I work with new medications that have to be monitored very closely to ensure those medication are safe for human subjects. Patients who experiences any adverse reactions are instructed to report any and all symptoms to me as soon as possible so I can submit those reactions for safety. While these reactions are very rare (medications need to be shown as safe before they are tested on humans), reactions occasionally do happen. If enough of these events are triggered, the medication is pulled by the FDA for safety reasons. These reactions are outliers as they are statistical anomalies that move the normal distribution of “safety”. The effects of the outliers on research are pretty potent. If there are enough outliers that state the medication is unsafe, the medication is not approved and does not get used in human subjects.

References

Ellenberg, J. (2015, January 30). New England’s incredible ball security is not impossible but also not meaningless. Retrieved from https://slate.com/culture/2015/01/new-england-fumbles-the-patriots-incredible-ball-security-is-not-impossible-but-its-also-not-meaningless.html

STUDENT TWO:

This week’s article was interesting to read, I am not much of a football fan but I have heard mention the patriots and the different things with the issues that have come up or perhaps the concerns.

Outliers are very interesting to look at as they are examples of very extreme and rare situations, and the representation they give isn’t a good one of the data as a whole. A scenario involving an outlier I thought of immediately is one of my cousin’s jobs. A lot of different things can affect her rating or her coworkers rating but one of the main things in their quality assurance scores. She currently works as a 911 dispatcher and they all have to maintain high quality assurance scores mainly because quality matters to an extreme while saving people’s lives. Something else that can affect is the rolled calls which happens when the call rings for more than 2 rings and it automatically goes to the next person that’s available for the call.

Here’s an example of an outlier with these performance scores is when the average score gets to 72.4 out of a total of 80 but then there can be a low score of 43.5. this would be an outlier score, it’s not near the average score and it can have a big effect on the average. If the low outlier would be taken out the average can go up to 76.8. so if only the average score is looked at that person might think they need to work on improving their quality. But if they look at the outliers they can see that there is one specific person needing to improve versus everyone.