Ethical Considerations in Business Statistics
“There are three types of lies – lies, damn lies, and statistics.” Benjamin Disraeli
According to Siddharth Kalla in an article entitled what is statistics, it is defined as a collection of mathematical techniques that help to analyze and present data. Statistical data is used by numerous professionals including scientists, physicians, economists and astronomers. With the global financial market becoming larger as businesses become globalized, statistical data or “big data” as it is referred to, is becoming increasingly important in the financial industry. Statistics enable businesses to plan production according to the taste of the costumers, the quality of the products can also be checked more efficiently by using statistical methods. This means that all the activities of the businesses based on statistical information. Statistics have aided in businesses becoming more profitable in varying industries. It has improved efficiency within businesses enabling them to target potential customers. Conversely, statistical information can also be manipulated either intentionally or unintentionally and this paper is will explore this concept and its effects. A 2009 investigative survey by Dr. Daniele Fanelli from The University of Edinburgh found that 33.7% of scientists surveyed admitted to questionable research practices, including modifying results to improve outcomes, subjective data interpretation, withholding analytical details and dropping observations because of gut feelings.
There are many ways in which the manipulation of statistical data can be achieved, the first unethical practice is faulty polling. The way questions are asked can evoke different responses in the reader. This is commonly referred to as loaded questions in which the interviewer asks a question in a manner that would provoke a certain emotion and dictate the response. The interviewer can also precede a question with a conditional statement
that is related to the question. For example, consider the following questions:
“Do you believe that you should be taxed so other citizens don’t have to work?”
“Given the rising cost of the middle class do you believe in government assistance?”
Questions should not be loaded with the opinions of the researchers because the responses may not express the true feeling of the interviewee and thus conclusions drawn will not be objective or useful to the study. These practices are most commonly used in political polls in order to manipulate the interviewees to sympathies with a particular view point.
The second unethical practice is purposeful bias characterized by deliberate attempt to influence data findings without even feigning professional accountability. Bias is most likely to take the form of data omissions or adjustments. This practice is most unethical because it deceives the receivers of the information to form opinions that are not based on facts, they only promote the agenda of the cultivator. Businesses are the most common culprit of this statistical manipulation. By generating misleading advertising data businesses persuade consumers to purchase their products over the competitors. One such example is the case of Colgate in 2007. The company was ordered by Advertising Standards Authority in the UK to abandon the claim that 80% of dentists recommended Colgate. While the research was carried out, the survey allowed dentists to select more than one option in terms of recommendations in which they in fact did. The research found that dentist recommended another brand just as much as Colgate. Further, the ASA also claimed that the scripts used for the survey informed the participants that the research was being performed by an independent research company, which was inherently false since they were being performed by Colgate.
It is evident that statistical data is one of the driving forces towards business developments success. One cannot overlook its contributions to various industries. Specially, the business industry has benefited from gathering information from various consumer habits sites including Facebook. This allows them to target trends, behaviors and capitalize on profitability. While, this information is extremely useful it can also be used to manipulate consumers opinions and even purchasing power when false statistical data is used in advertising.
Kalla, Siddharth, (2011 February). What is statistics. Explorable, Retrieved from: https://explorable.com/what-is-statistics.
Troster, Heiko, (2016 August). Misleading statistics examples – Discover the potential for misuse of statistics & data in the digital age. Datapine, Retreived from: https://www.datapine.com/blog/misleading-statistics-and-data/.