TRUSTING STATISTICS: Do you always trust the statistics you see in print? How about the ones you hear on the news or on your favorite talk show? What makes the statistics credible? For this question, I want you to tell me what personal criteria you would (or should) use to determine if you should believe reported statistics. Be specific, giving examples as needed.
Fake statistics are always in circulation. The statistics range from newspapers articles, television shows, and company surveys. Although some statistics are true, it is critical to set statistics standards as well as approach them with skepticism to avoid false information. This paper answers the question of which criteria to use to determine whether to believe statistics by giving examples.
The first criteria to use to determine whether to believe statistics is by ensuring that the statistical survey was not paid by party promoting the survey. For instance, if an auto manufacturer advertises that 90% of its cars are on the road, the survey should be paid by another unrelated party. If it is the auto manufacturer that funded the survey, then it is likely to be a self-selection study. The study enables a party to make money from the results of a survey. Thus, statistics from such a study cannot be trusted as they are in favor of the funding party.
Another criterion to determine whether to believe in statistics is by confirming that opinions are not biased. According to Pincock (2012), the statistics should not come from a voluntary survey where participants can choose to be included or not. For instance, a company might give a website link inviting the public to comment to they think of their products. The kind of survey is usually biased towards the participants who have mostly negative opinions. In other words, most participants will respond to the survey because they hate the company’s products. On the other hand, people who like the products will most likely not add any comments.
There are different motives for publishing various statistics. Thus, people should be aware of the existence of false statistics and create criteria to determine whether to believe them
Pincock, D. G. (2012). False detections: what they are and how to remove them from detection data. VEMCO Whitepaper Document DOC-004691, v03. Amirix Systems Inc., Halifax, NS, Canada.
by EssayRoyal, Dec. 6, 2019, 5:42 p.m.