Damned Lies and Statistics, or How to Lie with Statistics

  Too often, statistics are used to 'prove' some point or to persuade an audience to some particular point of view, without really being accurate, complete, or honest. This issue has been the subject of numerous texts. You may be interested in reading such titles as: Damned Lies and Statistics, or How to Lie with Statistics. To fulfill this discussion board activity, complete the following: Research one example where data analysis might have been misused or misapplied. Read about the example thoroughly so that you understand how analytics was used, and why it was problematic. Share your chosen example, documenting your source. Be sure to summarize the scenario thoroughly. Explain why use of analytics contributed to the problem. Discuss the consequences of the matter. Did the company/organization involved suffer any adverse consequences? If so, were the related to public opinion/trust, were they financial, were they punitive, etc.?

Sample Solution

   

Volkswagen emissions scandal

In 2015, Volkswagen was caught cheating on emissions tests for its diesel vehicles. The company had installed software in the vehicles that would detect when they were being tested and then switch to a cleaner emissions mode. This allowed the vehicles to pass emissions tests even though they were emitting much higher levels of pollutants in real-world driving conditions.

Full Answer Section

   

Volkswagen used data analysis to develop and implement this cheating software. The company's engineers used data from emissions tests to develop a detailed understanding of how the vehicles' emissions control systems worked. They then used this information to develop software that could manipulate the emissions control systems to produce lower emissions results during testing.

The use of data analysis in this way was clearly unethical and illegal. Volkswagen misled regulators and consumers about the true emissions performance of its vehicles. This resulted in significant financial costs for the company, including fines and penalties from governments around the world. The scandal also damaged Volkswagen's reputation and led to a decline in sales.

How the use of analytics contributed to the problem

The use of analytics contributed to the Volkswagen emissions scandal in two ways. First, it allowed the company to develop and implement the cheating software. Second, it allowed the company to hide the cheating from regulators and consumers for many years.

Without the use of analytics, Volkswagen would not have been able to develop the cheating software in the first place. The company's engineers needed to use data from emissions tests to understand how the vehicles' emissions control systems worked and how to manipulate them.

The use of analytics also allowed Volkswagen to hide the cheating from regulators and consumers. The company used the data from the emissions tests to create reports that showed that the vehicles were meeting emissions standards. This data was then used to convince regulators that the vehicles were clean and to reassure consumers that they were buying environmentally friendly vehicles.

Consequences of the matter

The Volkswagen emissions scandal had a number of negative consequences for the company.

Financially, the scandal cost Volkswagen billions of dollars in fines and penalties. The company also had to recall and repair millions of vehicles.

The scandal also damaged Volkswagen's reputation. The company was seen as having deceived its customers and regulators. This led to a decline in sales and a loss of trust from consumers and investors.

In addition to the financial and reputational consequences, Volkswagen also faced legal consequences for its actions. The company was sued by governments and consumers around the world. Volkswagen also faced criminal charges in the United States.

Conclusion

The Volkswagen emissions scandal is a clear example of how data analysis can be misused. The company used data analysis to develop and implement a cheating scheme that allowed it to deceive regulators and consumers about the true emissions performance of its vehicles. This resulted in significant financial, reputational, and legal consequences for the company.

The Volkswagen emissions scandal is a reminder that it is important to be critical of data analysis and to be aware of the potential for misuse. We should also be aware of the potential consequences of misusing data analysis, both for the individuals and organizations involved.

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