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International Journal of Scientific and Research Publications, Volume 9, Issue 6, June 2019 ISSN 22503153297Statistical Fallacy: A Menace to the Field of Science Kali Emmanuel Ogbonnaya×, Bénard
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Understand the common types of statistical fallacies such as cherry picking, correlation vs causation, and sample size bias.
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Evaluate the credibility of sources and data before drawing conclusions.
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Ensure that the data used is relevant, accurate, and representative of the population under study.
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Statistical fallacy refers to errors or misleading conclusions drawn from statistical data, which can pose a threat to sound decision-making and policy formulation.
Individuals or organizations that utilize statistical data for decision-making or reporting purposes may be required to address potential statistical fallacies in their analyses.
To address statistical fallacy, ensure accurate data collection, proper statistical methods, and thorough validation of results, documenting all processes and assumptions.
The purpose is to raise awareness about the risks of misinterpretation of statistical data and to promote accurate and responsible use of statistics.
Reports should include the nature of the statistical methods used, assumptions made, potential biases identified, and any limitations of the data presented.
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