Statistics

Posted by Isabelle Butler on January 22nd, 2020

Statistic is one of the strongest and one of the most effective weapons of media. The goal of the statistic is to provide short, quick and efficient information. However, statistic can be used to mislead intended or otherwise. The intended statistic manipulation can be used to present only limited data information, while unintended statistic manipulation is the result of incorrect usage of data information or faulty calculation.

The most common manipulation of statistic is when media confuse correlation for causation. For example, it was correlation between car accidents in New York and rains in Tokyo. The only correlation is the statistical relationship between these two events, but it does not mean that one event is the result of another.

One of the ways of statistic manipulation is providing average data. When researchers give a group of numbers, they usually simplify this information and give only the average figures. For instance, the costs of microwave own is 350 dollars, or the advertisement costs is 5 000 dollars. These figures are not correct; they are average and could be true or highly inaccurate. For example, according to data statistic the company’s X, the previous year budget was 250 000 dollars. However, by checking raw data, one will find that it was more than 2 millions dollars, while other statistic shows that it was only 50 000 dollars.

Another example of statistic manipulation is the usage of incomplete statistic. For example, the survey showed that 40 % of population prefers potato chips to rice chips. Nonetheless, this information could not be trustworthy. The interrogated people are only the part of the general population. In fact, it does not mean that this information is correct and complete. If you ask other ten people, the survey may show contrary result, and now 60 % of population prefers rice chips, and not potato ones. Thus, the survey statistic is always something relative and such information cannot be viewed as authoritative. Another example of incomplete statistic is when the used information does not respond to the current data. The new series of printer uses 20 % less ink. The information is incomplete because there are no any evidences to what type of printers this statistic is related to. Does this printer use 20 % less ink than all other printers, whether it relates to the previous models of this printer, or perhaps the statistic says about the printers that were used a decade ago? In this case the information is incomplete because there is no detail data about the results of analysis for this survey.

The mentioned examples show cases when statistic information is manipulated unwittingly. The reason for such statistic manipulation is lack of information or lack of awareness. Nevertheless, statistic manipulation can be used indented to embarrass people. The usage of the word “average” does not have the same meaning as in math. It does not mean that the figures were calculated and the researchers received the average meaning of this figure. In fact, it means the same as “approximately”, and as a rule, it is always false. The given way of manipulation is often used to attract the customers, proposing them low price. For example, the average cost of the house is 60 000 dollars. The potential customer suggests that this price is true, but later it is discovered that the price of the house is 70 000 dollars. Actually, it was a way of customers’ invitation, but in fact, it is a fraud.

Another example of statistic manipulation is the usage of such term as “99 % accurate”. As a rule, nobody gives 100 % guarantee, and thus, it is used to say 99 % because there is always a miracle chance that this statistic is failed. However, in other cases, 99 % means that there is one chance of 100. Thus, such statistic method does not give proper information and there is always a chance that this statistic is a lie.

The statistic information can be used incorrectly or in a wrong manner. For instance, the researchers made an analysis and discovered that those citizens, who live near electric lines, have more chances to ill with cancer. In fact, the researchers gathered information about the people, who live in this area and it showed that the cancer rate was higher than in other locations. According to this data, they made a conclusion that the reason is the electric lines and their survey is based on the researchers’ suggestion, but not on real facts. The mentioned case shows that data information cannot be used in a proper way, and the statistic cannot be reliable.

Statistic always means something relative, and thus, it cannot be used as the only trustworthy source of information. Raw data usually shows distinctively opposite information, so it is better to use several statistic surveys to have the whole picture of the situation. Nonetheless, statistic manipulation does not always mean the unintended process. Sometimes statistic manipulation is used to influence the society opinion, or to achieve some commercial targets. Statistic can be manipulated to misinform people concerning some political issues, when real facts may bring more harm than benefit. In this case, statistic manipulation can be justified, but in the majority of cases, it is considered to be abuse of rights. Media use it to manipulate people’s opinion or to present deceptive information.

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