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# Misuse of Statistics

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Introduction

Statistics can be very helpful in providing a powerful interpretation of reality but can also 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 can we determine whether to accept the statistical evidence that is presented to us. These days statistics are used everywhere. Whether it is in politics, economics, sciences or as pure mathematical discipline, much data is presented in the form of statistics. Statistics can offer a great and precise tool to interpret reality, but they are also easy to manipulate and push into certain outcomes. As already Winston churchill said "the only statistics you can trust are those you falsified yourself". Although it is not possible to falsify statistics in the pure mathematical form, where statistics can only be wrong calculated or based on wrong data, in many other parts statistics can be falsified to come to certain results. One of the main problem with statistics is that they can be mathematically correct but still don't represent the reality. ...read more.

Middle

A classic error done in statistics is that people conclude from a correlation between two events to a causality (one controlling the other). Say A and B often occur together and one concludes that then A causes B. Or in a more concrete example 'Men with less scalp hair earn more money'. The creator of this statistic observed two things that often occur together and concluded that one therefor causes the other. In fact there is only a third factor that makes men with less scalp hair earn more money which is simply that their older and had more time to make career. This is a common mistake in sciences for example when the scientist observes to phenomena that occur together and then jumps to the wrong conclusion one would cause the other. Another reason why statistics are easy to misuse, is the fact that they are normally based on surveys. This makes it very easy for the originator to drive the statistic into a certain direction, as he can determine the origin of the data used in the statistic. ...read more.

Conclusion

There is also another factor that can falsify statistics. So is for example the use of words crucial for the outcome of a statistic. Take for example the following question: "Is flying safe?". What is meant by safe? Another thing that can change the result is if a personal question is being asked. If someone asks for example "do you punch your children" most people are going to deny it even if they do. Although there are many ways in which a statistic can be accidently or knowingly falsified they are a great tool to represent a useful picture of reality. If they are organised in the right way statistics can be very useful in every area of Knowledge, whether it is science, politics or purely mathematical. But how can you make sure that a statistic is set up in the right way? How do we protect our selves from falsified statistics? These fife steps should help to detect at least some misuses of statistics: Who says so? What bias does the speaker have? How do they know? ( samples, percent returns etc.) What is missing? (look out for what has not been said) Did somebody change the subject? (The reply might not be to the question) Does it make sense? ...read more.

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