Bad statistics result from data misuse and lead to misleading information which cannot be relied upon. One of the bad statistics mentioned in the video Don't Be Fooled by Bad Statistics is the poorly collected data whereby the respondents used to provide the data do not represent the interest of the larger population. Another form of bad statistics described is the use of leading questions which prompt the respondents to concur with the questions being asked. In this case, the respondents lack first-hand information about the topic being researched and just give the answer they think is correct. The video also terms the use of the wrong center as another bad statistic where the data captured emanates from other secondary sources other than the one being investigated.
Reasons for Avoiding Bad Statistics
Bad statistics should be avoided since they give wrong information and can mislead people when making decisions (Brezina, 2018). For example, students often search the suitability of a course before they enroll. Providing bad statistics about the demand of graduates in that field may make people choose careers with fewer demands leading to wastage of time and frustrations. Also, bad statistics should be avoided as they lead to unfavorable policies. For example, bad statistics on the prevalence of road accidents can lead to the introduction of speed limits which introduces inconvenience the road users.
Examples of Bad Statistics
An example of the poorly collected data is when marketers use online newsletters to inquire potential consumers about a new product they wish to introduce (Pride, Hughes, & Kapoor, 2010). In the long run, the marketers will collect wrong statistics since not all subscribers are potential buyers. The use of leading questions is another instance of bad statistics and can be explained using the case of the US president Donald Trump. When people are asked whether Trump fits the president position, most of the respondents give a No as the answer. However, their responses emanate from the negative image of Trump in social media (Farnsworth, Lichter, & Schats, 2017). An example of the misuse of centers is the use of data for school dropouts to develop statics of students who drop due to drug use. The statistics will be wrong since there are other causes of school dropouts which include academic failure, financial difficulties, cases of disability and mental illnesses (Franklin & Fong, 2011).
The Michael Jordan Fallacy
The Michael Jordan fallacy is the inclusion of his wealth gained from his basketball career to calculate the average salary of the students in the University of North Carolina who attained geography majors in 1986 (Dressler, 2011). This study states that the students had average starting salaries of two hundred and fifty dollars. Such a study renders the geography major which he attained on demand in the employment sector and the students who pursue the major are sure of accumulating a lot of wealth.
Relationship Between the Fallacy and Statistics
This fallacy is related to statistics since Michael Jordan's wealth from basketball is included when calculating the average salaries for the students who graduated with geography majors (Dressler, 2011). The inclusion of Michael Jordan's starting salary in the statistics provides false information since he did not attain his salary using his educational credentials.
Factoring in students who took different fields from the one they attained their major in will boost the average salaries earned and provide wrong data. It is also evident that individuals involved in sports are awarded huge salaries compared to employees in the cooperate world. In this case, the research should exclude Michael Jordan and use data for students who are in their fields of specialization.
Brezina, V. (2018). Statistics in corpus linguistics: A practical guide. Cornwall: TJ international LTD.
Dressler, E. (2011). Don't be fooled by bad statistics. [Video file]. Retrieved from https://www.youtube.com/embed/jguYUbcIv8c.
Farnsworth, S., Lichter, S., & Schats, R. (2017). News coverage of trump is really, really negative. Even on Fox News. Retrieved from https://www.washingtonpost.com/news/monkey-cage/wp/2017/02/28/news-coverage-of-trump-is-really-really-negative-even-on-fox-news/?noredirect=on&utm_term=.433558eb9044.
Franklin, C., & Fong, R. (2011). The church leader's counselling resource book: A guide to mental health and social problems. New York: Oxford University press, Inc.
Pride, W. M., Hughes, R. J., & Kapoor, J. R. (2010). Business. Australia: South-Western/Cengage Learning.
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