What are the Limits of Statistics?
Statistics can help accurately describe social and behavioral phenomena (if the underlying measures are accurate), but they can also misrepresent them. Statistics can be manipulated or, at least, their limitations can be obfuscated when communicating results.
Develop an original response describing a real-world example where statistics might be used to misrepresent data or where they might not fully represent an underlying truth without adequate disclosure of the limitations of what the data can and can’t say about something. You might discuss: political polls with wide errors of margin, earnings before interest, taxes, depreciation, and amortization (EBITDA) projections for a tech startup seeking venture capital, or patient satisfaction scores across a healthcare system.
Or, think of your own example and share it with the class. For whatever example you choose, use the Module 1 readings to support your points, discussing what factors might need to be “hedged” with limitations when applying statistics to the situation.
Book Title The Tao of statistics: A path to understanding (with no math)
Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences
What are the Limits of Statistics?
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What are the Limits of Statistics?
A real-world example where statistics might be used to misrepresent data is in patient satisfaction scores across a healthcare system. For instance, in a situation where a healthcare organization targets to improve its image and hence attract more patients, the organization decides to display scores on patient satisfaction as a marketing strategy. They report that they have attained a 93% on average satisfaction score. In this scenario, the healthcare system, leaving out data on limitations, might use statistics to misrepresent data in various ways.
One of these ways is through selective reporting, where they report only the positive aspect (Wagner et al., 2018). In this case, the system only reports the average satisfaction score and leaves out areas with poor scores, such as long waiting durations. They focus on the positive side and neglect areas that need improvements.
Another way they might use statist...