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Statistics can be very helpful in providing a powerful interpretation of reality but also can be used to distort our understanding. Discuss some of the ways in which statistics can be used or misused in different Areas of Knowledge to assist and mislead us, and how we can determine whether to accept the statistical evidence that is presented to us. In this essay I shall discuss under what circumstances statistics can be a useful tool that helps us understand things easier as well as how it can be misleading in different Areas of Knowledge.

Furthermore, I will try to demonstrate how statistics affect the Ways of Knowing and hope to show that there is pretty much of both use and abuse of them in our everyday life. The old myth about storks bringing the babies has been repeated so many times that there has to be something more to it – true or false? Of course, we all know that the myth is nonsense, but how did it come up? My dad went to a conference once which was among other things about statistics. One of the lecturers entertained the audience by bringing up a statistical analysis of the old “stork-brings-babies” myth.

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According to him, one could, in principle, mathematically “prove” it, strictly following the rules of statistics. Thereby, the established notion about sexual reproduction would be anachronistic, and the connection between sexual intercourse and childbirth would just be based on widespread suspicion, and developed just on the basis of not entirely certain theories – theories that only rest upon coincidental, over-interpreted observations. The correlation between natality and stork population was inspected and “proven” by an epidemiological investigation within a defined frame of time and a limited area and “validated” by analysis of new data.

Although those “facts” applied only to a certain area, the correlation coefficient of almost 1 was very impressive. That means it is almost 100% certain, but it does not necessarily prove, that the storks bring babies, at least to that area. However, it is a classic example of how correlation, a very often used type of statistics, can be misleading. This is indicative of “illusory correlation” with uncertain causality.

This kind of statistic analysis could have a great impact on several Areas of Knowledge, e. g. biology, because if we were to believe in this “statistically verified” myth, we would question sexual reproduction. As “ethics involves a discussion of the distinctions between right and wrong” statistics play an important role, too, because correlation, for example, creates awareness of different possibilities. Hereby, it has an impact on our Ways of Knowing. Expectations, assumptions and beliefs effect perception by creating an image of a “truth” for oneself. Hence, statistics might have a great effect on perception, as it presents alternatives which differ from what one might have thought.

This would mean that a person has at least two options to choose from what he or she should believe. Where do babies come from? By using reason one comes to a decision. As a biology student, I know that sexual reproduction is the reason of childbirth, and that the correlation is based on coincidental, but not causal factors, perhaps, like the increasing number of rooftops. “More houses with rooftops meant more people and so more babies. More rooftops also meant more birds, which nested on the high, safe, level surfaces.

When rooftops were redesigned, or people moved into apartment dwellings, the baby-stork correlation disappeared. ” Other factors of the illusory correlation could have been heat – “Where there were babies, a fire was kept going all day long, so the birds stopped by for warmth” or that “Human births are more frequent at certain times of the year, and these just happen to coincide with stork nestings”. The modern society is surrounded by statistics. That is, statistics are used as a powerful tool to add a “scientific argument” by media such as marketing and propaganda.

However, when indeed based on scientific evidence, it may lead to a sustained change of consciousness and habits. For example, if we take a look at anti-smoking campaigns, we will see that the main argument against smoking will be the possibility of getting cancer. This argument is used, because it is based on statistics which provide evidence that smoking very often leads to cancer. According to the U. S. Department of Health and Human Services “Lung cancer is the leading cause of cancer death, and cigarette smoking causes most cases”.

Another statement is even more impressive and often used for the purpose to persuade smokers to quit: “Compared to nonsmokers, men who smoke are about 23 times more likely to develop lung cancer and women who smoke are about 13 time more likely. Smoking causes 90% of lung cancer deaths in men and almost 80% in women. ” Unfortunately, this does not exclude the chance of a nonsmoker to get cancer. Statistics that are used for propaganda usually have the intention to inform or convince people of someone’s opinion about something.

In other words, statistics can be used to reveal the “truth”, and in this case it is probably for the better, if one relies on the statistics about cancer. The so called “truth” in this case is an informative statement supported by statistical data that intends to show people the potential consequences of smoking. Hence, society receives the message that “smoking = bad” due to this presentation of statistics. People use to great extent emotions to decide for themselves whether something is “right” or “wrong. Thus, statistics might influence emotions as it makes us believe that smoking is not good.

Furthermore, it affects reason, as it could have an impact on a person’s decision whether to smoke or not which might be different without the presented data. This is an example of statistics being used to assist us in different Areas of Knowledge. Each Area of Knowledge is based on several sets of rules and carries its own truth. When we relate the example of smoking and its following statistics about cancer to mathematics as a science, we tend to accept it as “truth”. That is so, because mathematics is generally perceived as a solid science that primarily uses numbers and symbols.

We usually tend to believe statistics, as conclusions and results are presented to us in the same clear language. Statistics are a very important part of mathematics that allows us to make investigations of complex quantitatve data. Basically, to humans mathematics seems reasonable, so we rely on it without much doubt. However, this arranges the possibilty of statistics misleading us, and we are responsible for ourselves to determine whether to believe something or not. Smoking leading to cancer has been propely investigated, including scientific experiments.

The statistics are primarily used as language to make us understand and become aware of facts. In the first example, “stork-brings-babies”, it is quite obvious that the conclusion is solely based on the correlation of unrelated data. In this case, correlation is clearly a misuse of statistics in natural sciences, as we could easily turn the example around – that means we would have a “baby-brings-stork” myth, as the correlation would be true for either event. Yet, it would be possible to prove whether the myth is correct or not by testing it scientifically.

One would only have to prevent storks from nesting in the tested area, and see whether babies would still be born or not. Clearly, this example has no effect on our understanding of where the babies come from. However, it demonstrates the potential power of statistics to fundamentally mislead us. In everyday life, statistics sometimes appear to be used to convince us, particularly in situations that may require just a “final kick”, for example, to make us buy something. I remember an advertisement of a lottery claiming that almost 90% of the tickets would be winning.

It suggested that it would be foolish not to buy many tickets and miss the opportunity of winning a lot of money. This had to be a lie! But no, it was true and the calculation was presented in the ad. However, the cost of a ticket was many times higher than almost all the prizes that could be won. This part of the calculation was left out of the ad, of course. It is quite obvious that the use of statistics, especially, but not exclusively, in the area of commercials, has been discovered as a very efficient way to influence people’s decisions. In my view, this trick links, in a subtle way, different Areas of Knowledge.

While we might emotionally tend to have an opinion or desire, it may rationally seem incorrect. The use of statistics clearly helps to remove the doubts about the logic of a desire. Of course, everybody would like to just win a lot of money. Therefore, it is emotionally understandable to wish to buy a lottery ticket, even though the chances are negligible. Being supplied with a seemingly rational argument it will be much easier to surrender to the emotion. Although there seems to be increasing awareness of the use of statistics as a method to specifically influence our thinking, it still has undoubtedly success.

Nevertheless, the plain, intentionally misleading use of statistics has probably taught us to exercise more caution when confronted with studies or claims that are allegedly based on scientific evidence. As a result, instead of properly evaluating the information, we might first of all ask the question which purpose it might possibly serve. Sadly, with regard to true scientific investigations and their communication, I am concerned that people might become too sceptical and have less appreciation or even less interest in new discoveries.

On the other hand, the substantial decline of the number of smokers in many countries is, in the end, a result of persuasive scientific work. I believe therefore that the appropriate application of statistics is still an essential and recognized part of science in different Areas of Knowledge. On the contrary, statistics misused to strengthen false arguments may have temporary success, but it will become increasingly difficult to make people believe in them.

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