Chrystal Murphey
I like your post because it is well organized. I think it covers all the grounds in terms of what one needs to know regarding outliers and their role in statistical analysis. However, the post does not explain or give a small definition of what an outlier is, and I think this is important to help the reader understand it and its influence. An outlier is a data point that is significantly out of agreement with other observations, and it can be a result of variability or an error in measurement. However, in certain cases, it is caused by real happenings. Among the impressive things I see in the discussion on the uniqueness of outliers is that it differs from most data. The statement is supposed to be the definition of outliers, and it should have been the first or second sentence in the post.
Chhoeut
The explanation of real situations where outliers are experiences is impressive. The post uses demonstration with real-life examples, which is impressive in helping someone understand outliers deeper. A town hosting an event will flood with people, and businesses are expected to cash in from the event. However, the fact that the event is not regularly held there implies that businesses that have benefited from the event will experience an unusual surge in sales for the period of the event. The case of Starwood Hotels and Resort is an example of how business management can remain sensitive to outliers and make proper management decisions. As the post demonstrates, possible negative consequences from disregarding outliers include incorrect staffing or investor confidence loss. I also agree that bar graphs and histograms as reliable in identifying outliers because they appear clearly. Using Boxplot, for example, will make it difficult to identify outliers. The post is comprehensive in general, and that what makes is great.
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