Misuse of Statistics: Discussion on Misuse of Statixtics

Misuse of Statistics: Discussion on Misuse of Statixtics

admin / February 15, 2019

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Misuse of Statistics

Discussion

we will see in the next 12 weeks, statistics when used correctly can be a very powerful tool in managerial decision making.

Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, etc…

As such a strong tool, statistics is often misused. Everyone has heard the joke (?) about the statistician who drowned in a river with an average depth of 3 feet or the person who boarded a plane with a bomb because “the odds of two bombs on the same plane are lower than one in one millionth”.

Can you find examples in the popular press of misuse of statistics?

I’m sure some of you have heard someone say “73% of statistics are made up on the spot.” I’m not sure what the actual percentage is but I made that one up. I’ve heard things like this many times and it has always made me skeptical of statistics, especially when I cannot see the data to back it up. I think in some cases people will tweak the way they present their data in order to prove their point. They will choose the best data and format that supports their claim and leave out the data that does not.

A few ways that statistics can be misleading include: faulty polling, misleading visual visualizations, bias, and flawed correlations (Lebied, 2018). I found an example of this on a toothpaste add. The toothpaste brand Colgate advertised that 80% of dentists recommended this toothpaste. However, they failed to mention that the poll allowed dentists to choose a brand of toothpaste from a list of different brands (Lebied, 2018). This could be misleading because Colgate could have purposely made a list of brands that dentist were less likely to choose compared to Colgate. This is a case of bias and possibly faulty polling (Lebied, 2018). As I mentioned before, sometimes people will skew their data to help prove their case and I think this is a good example of that.

Reference

Lebied, M. (2018). Misleading statistics examples – Discover the potential for misuse of statistics & data in the digital age. Data Pine. Retrieved from https://www.datapine.com/blog/misleading-statistics-and-data/

Whether intentionally or not, statistics can be misleading or misused. Some common types of misuse are faulty polling, flawed correlations, data fishing, misleading data visualization, purposeful and selective bias, and using percentage change in combination with a small sample size (Lebied, 2018). One example of misused statistics was recorded in 2007. In the United Kingdom, Colgate claimed that more than 80% of dentists recommend their brand. The claim was based on surveys of dentists and hygienists carried out by the manufacturer. This was a misrepresentation because the participants were allowed to select one or more toothpaste brands. Consumers may interpret that claim as 80 percent of dentists recommend Colgate toothpaste over to all other brands when in fact, other brands were recommended almost as much as the Colgate by the dentists surveyed.

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