Confusing Statistics

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 fraud is glaring. Stats are mostly wrong in the first 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 of certain data such as DNA and other probability models.

The legal system should be less reliant on these forms of argument as there is too much room for error when dealing with maters of justice and liberty. "Stated simply, it is unethical to carry out bad scientific experiments. Statistical methods are one aspect of this. However praiseworthy a study may be from other points-of-view, if the statistical aspects are substandard then the research will be unethical," (Altman, 1980). The numbers in statistical analysis can be made to perform many functions. Essentially stats serve two purposes.

The first is to describe and the other is to predict the future. The future itself is not a tangible or real idea, it is abstract, therefore any use of statistical inference will refer to a completely abstract idea. Misuse of statistics occurs when statisticians fashion themselves as prophetic fortune tellers. Since many people do not understand the manipulation of the numbers that is necessary with types of analysis, it is very simple to fool and cheat people using these numeric symbols.

The need to predict events is important and can provide a practical means of understanding the world around us. But when statistical information.