Confusing Statistics Essay

PAGES
2
WORDS
759
Cite

Statistics in Relationships It is important to understand the limitations of mathematics, number and statistics. Stats and numbers play a larger role in assigning value to things in today's society. The entire monetary system is based in this statistical mire. The idea of stats being viewed as only a tool or artifact of technology can prevent the misuse of this concept. The following will address several of these examples to demonstrate the essence and true value of statistics as merely an extension of the individual who is applying this type of numeric manipulation.

The famous author Mark Twain once described statistics being more confusing than actual lying and lies. Bad statistics are found everywhere and there are many examples of how things can be confused for the truth. Bayes Theorem describes the incidents of conditional probability. But inherent in this model, the original probability is assumed to be known. If this error was discovered by doctors, the incidence of false positives in cancer would soon skyrocket and actual cancer rates would be significantly reduced.

Compounding interest rates applied to credit cards and loans seem to be a misuse of statistics. Percentage rates seem very low, but when mathematical statistical modeling is applied, the extent of the place, unless a clear and well defined application with assumptions and premises clearly laid out, the analysis may not be valid.
Coontz (2013) wrote "But averages can be misleading when a distribution is heavily skewed at one end, with a small number of unrepresentative outliers pulling the average in their direction. In 2011, for example, the average income of the 7,878 households in Steubenville, Ohio, was $46,341. But if just two people, Warren Buffett and Oprah Winfrey, relocated to that city, the average household income in Steubenville would rise 62% overnight, to $75,263 per household." This examples highlights simply how averages can be used to mislead into a certain argument.

Stats are often used too often in determining winners and losers in sports as well. The win loss records are the only stats that matter in deciding who is a champion. Sometimes theses stats overshadow the very purpose of competition in the first place. Hitting a home run means nothing if the team loses the game in the long run.

Stats are often misused in the legal arena as well. Life and death is often decided due to statistical manipulation…

Sources Used in Documents:

References

Altman, D.G. (1980). Statistics and ethics in medical research. Misuse of statistics is unethical. BMJ, 281(6249), 1182-1184.

Coontz, S. (2013). When Numbers Mislead. The New York Times, 25 May 2013. Retrieved from http://www.nytimes.com/2013/05/26/opinion/sunday/when-numbers-mislead.html

Lewis, D.D. (1998). Naive (Bayes) at forty: The independence assumption in information retrieval. In Machine learning: ECML-98 (pp. 4-15). Springer Berlin Heidelberg.


Cite this Document:

"Confusing Statistics" (2015, April 10) Retrieved April 18, 2024, from
https://www.paperdue.com/essay/confusing-statistics-2150614

"Confusing Statistics" 10 April 2015. Web.18 April. 2024. <
https://www.paperdue.com/essay/confusing-statistics-2150614>

"Confusing Statistics", 10 April 2015, Accessed.18 April. 2024,
https://www.paperdue.com/essay/confusing-statistics-2150614

Related Documents

One of the most common fallacies is to confuse correlation with causation, but the two are actually distinct. My demonstrating that construction of snowmen and outbreak of acne occur simultaneously does not mean that snowmen produce acne. It may imply an underlying matter, such as the snow itself may contain some component that may instigate the outbreak, or the children who build the snowmen may be particularly vulnerable to

Statistics to Mislead Statistics can be misleading. People can use misleading statistics to persuade others to buy a product or share their point-of-view. Britain's Sunday Times, for example, alerted readers more than a decade ago to this tactic, showing that insurance companies often use misleading figures to scare consumers into buying expensive coverage they may never need (Cooper, 2001). In Mathematics in Our World, Bluman (2011) provides numerous examples of

confused as to how you derived the population mean of 1 +/- .010, as the population mean (not the sample average mean) is given as 1.008. Also, the customer needs the sample mean to be within 90% of one inch (1 +/- .1, not 1 +/- .01); a simple analysis of the normal distribution based around a mean of 1.008 inches shows that this would easily be accomplished, as

Thus, holders of this statistically-driven information holds the 'power' over the general public, succeeding in influencing the general public's opinion and feelings about a specific issue or social concern. Best reflects in his book his advocacy for correct usage of social statistics, as he knows the critical role that numbers and statistics play in swaying not only general opinion and perception, but ultimately, in the public's perception of the

Being able to express statistical results in ways non-statisticians can understand, and explaining those results correctly in language that does not mislead or confuse is becoming a lost art, if the popular media are any indication. Entrepreneurs will use these visual display techniques to increase productivity, notice patterns that may go unrecognized in tabular or numerical reporting, and communicate results quickly without requiring extensive and subjective verbal explanation. Inferential statistics

teaching of statistics and problems encountered in such teaching. Teaching Statistics: An Annotated Bibliography Albert, Jim. Teaching Statistics Using Baseball. New York: The Mathematical Association of America. 2003. Baseball is a very statistically oriented sport, more so than any other sport. This book applies statistical methods and techniques to the game of baseball. Since students often have difficulty learning statistics because they are presented with examples that they have no frame of