Why are the mean and median so different in this case?

The median and mean of a set of data can often times be quite different from one another. One example of this is household income in the United States. According to the U.S. Census Bureau’s 2014 Annual Social and Economic Supplement, mean household income in 2014 was $72, 641, while median household income was $51,939.

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Why are the mean and median so different in this case? Find another example of a statistic in which the mean and median values would be expected to be quite different and explain the difference.

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Week 2 Discussion Prompt 1 Math
The household income data, in this case, can be termed as “highly skewed” given the significant difference between the mean | GET AN EXPERT FOR YOUR ASSIGNMENT | differing mean and median, the U.S. household income data was calculated differently than it is the norm. For example, since it exhibits a “highly skewed” data, it means most of the respective income data, while being calculated, were clustered near one extreme, and a relatively few income data near another (Barbosa et al., 2017). Therefore, considering the means are more sensitive to values on the extreme than medians, the mean income score tends to be closer to the more populated extreme compared to the median. This explains the differences between mean and median of the | GET AN EXPERT FOR YOUR ASSIGNMENT | with an outlier. The outlier affects the average mean more than it does on the median. According to Holt & Scariano (2009), an outlier can throw off the mean of a data set, more so if the dataset is small. While the above…