The Central Limit Theorem (CLT)

The Central Limit Theorem (CLT) may appear a bit magical, at first. However, it is a cornerstone of modern
statistical analysis. There are numerous visualizations of the CLT; of which, http://mfviz.com/central-limit/
provides an excellent interactive visualization of the CLT. Visit http://mfviz.com/central-limit/ and experience the
CLT.
After experiencing and learning about the CLT, make sure you understand the requirements of the CLT. These
requirements must be satisfied before applying the CLT:
The data must be the result of random sampling.
Samples should be independent. (Or, one sample should not influence another sample.)
The sample size should be at most 10% of the population.
The sample size should be at least 30.
Goal. Using the visualization and the requirements of the CLT, find a news article containing statistics you think
may benefit from an application of the CLT. Apply the CLT to the information in the article and draw inferences,
as appropriate. Also, justify your application of the CLT by arguing how your article and inference met the
requirements of the CLT.