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Logical Fallacy of Biased Statistics / Biased Statistics / Loaded Sample / Prejudiced Statistics / Prejudiced sample / Loaded Statistics / Biased Induction / Biased Generalization / Unrepresentative Sample / Unrepresentative GeneralizationFallacy of biased statistics is one of the many smokescreens that are used to cover the fact that the reasoning is based on one of the three fallacies of Agrippa's trilemma. Whenever a logical fallacy is committed, the fallacy has its roots in Agrippa's trilemma. All human thought (without Divine revelation) is based on one of three unhappy possibilities. These three possibilities are infinite regress, circular reasoning, or axiomatic thinking. This problem is known as Agrippa's trilemma. Some have claimed that only logic and math can be known without Divine revelation; however, that is not true. There is no reason to trust either logic or math without Divine revelation. Science is also limited to the pragmatic because of the weakness on human reasoning, which is known as Agrippa's trilemma. The logical fallacy of biased statistics occurs when a generalization is made based on statistics that are inadequate for the generalization to be known. As with all fallacies, the person who is fooling others with the fallacy may or may not be fooled by the fallacy as well. Examples of the Logical Fallacy of Biased Statistics / Biased Statistics / Loaded Sample / Prejudiced Statistics / Prejudiced sample / Loaded Statistics / Biased Induction / Biased Generalization / Unrepresentative Sample / Unrepresentative Generalization
Friends tend to select friends who are like-minded. This is a very biased sample. The Kinsey Report The Kinsey Report was based on volunteer bias, disproportionate sampling from some groups (strata) with high rates, inappropriate analytical methods, misleading definitions, and possibly, intentional fraud due to personal bias. Yet it has impacted U.S. morality, laws, and thinking dramatically.
This remark asserts something that is statistical in nature. The person making the remark is not basing it on sound research. This has been tested by a liberal professor, Dan Kahan, who, through a government-funded grant, did a study of Tea Party members as compared with non-Tea Party members. Kahan was surprised to find that the base rate puts Tea Party members measurably higher in their understanding of science. https://www.ijreview.com/2013/10/87474-yale-professors-surprising-discovery-tea-party-supporters-scientifically-literate/
The statistics don’t support this. In an extreme case, someone may even say that they don’t care about the statistics and stick to their guns on the issue. Polls are often cleverly worded to get a certain result so that they can be used to mold public opinion. Figures don’t lie, but liars figure. 
How can we know anything about anything? That’s the real question |
Other Pages in this sectionMisused Statistics Innumeracy Clustering Illusion Bad Statistical Data Biased Statistical Method Biased Calculation Biased Conclusion from Statistics Biased Reporting of Statistics Generalizing from a Hypostatization Error in Sampling Avoiding Specific Numbers False Precision Self-Selected Biased Sample Statistical Apples and Oranges Ludic Fallacy Fishing for Data Base Rate Neglect Isolated Examples Hasty Generalization Small Sample Size Bias General Rule Fallacy Specificity Overwhelming Exception Stereotyping Sweeping Generalization Gambler\'s Fallacy Appeal to Possibility Appeal to Infinite Possibilities Texas Sharpshooter Fallacy Misuse of Averages Recently Viewed |
