The ethical dilemma in the “Honest Harry” scenario includes receiving a sample from people who may be prejudiced as opposed to finding providers of more objective data. It corresponds with the Personal Integrity and Accountability rule from Ethical Guidelines for Statistical Practice. According to the American Statistical Association (2018), the statistician must identify any possibility of favoritism or preference that may affect the objectivity of the survey results. A part of the dilemma is the choice between surveying as proposed or choosing another method that would be more reliable and, consequently, more unlikely to have unfavorable results.
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Possible Undesirable Consequences
Receiving the sample from organic food store clients may result in the majority of people favoring the proposed idea of the river conservation based on their personal preferences. People who Harry interacts with buy organic food, and there is a possibility that they prefer such goods for specific reasons (Sharpe et al., 2014). For example, they can be concerned about the environment, traditional agriculture methods, or the use of chemicals in food production. Notably, the survey is focused on the restoration of a river polluted with chemicals due to agricultural discharge. While it cannot be guaranteed that all organic food customers are environmentally conscious, the possibility of favoring a particular option must be taken into account.
The idea of interviewing shop customers is reasonable, as it allows collecting enough data in a short period. However, the visitors of an organic food store are likely to favor a specific position in the survey, which makes them unreliable. An ethical solution would be to acknowledge the limitations of Harry’s store and choose another location for the sample collection, preferably the one that does not have any association with the survey subject.
American Statistical Association. (2018). Ethical guidelines for statistical practice. Web.
Sharpe, N. D., De Veaux, R. D., & Velleman, P. F. (2014). Business statistics (3rd ed.). Pearson.