Give me a real-life example of a data distribution that you think is approximately normal, but with a large spread (i.e. large standard deviation). What reasons or conditions attribute to the large variation? What about a data distribution that you think is approximately normal, but with a very small spread? What limitations prevent the data from having a larger variation?

A data distribution with a relatively large spread might involve broadband access across the United States. Many variables account for the range of quality internet in America. Reasons could include a state’s economic makeup and the differing priorities of local governments.

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One kind of data distribution to consider evaluating would be broadband access across the United States. This data set might produce some variation upon further inspection. A 2018 study shows that almost 98 percent of New Yorkers have access to broadband, yet only 70 percent of Mississippi residents have access to high speed internet. When thinking about reasons for the data variations, consider the economic constitution of the states in question. New York has many media and tech companies. These companies—and the people who work for them—need reliable access to quality internet to perform their duties. In Mississippi—a state not exactly known for big media and tech corporations—broadband might be less of an economic imperative.

Another variable is the priorities of the governments themselves. Some local governments put more emphasis on access to the internet. The mayor of New York City, for instance, seems to believe that access to broadband and wifi is a key part of a fair and just community. In the twenty-first century, regardless of a person’s job, solid internet access seems to be a crucial part of everyday life. Of course, not all governments and states might feel this way.

Another data distribution that could produce a thought-provoking mean and standard deviation is opium overdoses in the United States. With this set of data, consider how a state’s specific economic makeup and healthcare system could result in higher opium fatalities.

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