http://www-stat.wharton.upenn.edu/~steele/Publications/PDF/TN148.pdf How to Lie
ID: 3011802 • Letter: H
Question
http://www-stat.wharton.upenn.edu/~steele/Publications/PDF/TN148.pdf
How to Lie with Statistics is a popular book written by Darrell Huff in the 1950s. Looking at the Empirical Rule, give some examples of how companies, academics, and individuals are able to lie (or at least exaggerate) with statistics.
empirical rule: http://www.statisticshowto.com/empirical-rule-2/
Empirical Rule
The empirical rule, also known as the three-sigma rule or the 68-95-99.7 rule, provides a quick estimate of the spread of data in a normal distribution given the mean and standard deviation. Specifically, the empirical rule states that for a normal distribution:
68% of the data will fall within one standard deviation of the mean.
95% of the data will fall within two standard deviations of the mean.
Almost all (99.7%) of the data will fall within three standard deviations of the mean.
The empirical rule is used as a rough gauge of normality. When a number of data points fall outside the three standard deviation range, it can indicate non-normal distributions.
Explanation / Answer
I will take an example of global scale here. Its exaggerated that the age of popualation of earth is normally distributed,
The exraggeration is well found in the fact that there is a skew in the distribution and therefore the normal distribution' empirical rule doesn't hold true in this case.
Actually, given the concentration of population in India and China, and ( also given the fact that the average age here quiet low) the distribution is skwewed towards right. Therefore, if you were to see the disttribution and try to take out the area under curve or probability using empirical values then your method may fail, given the skew.
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