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Logical Fallacy of Error in Sampling

 

Logical Fallacy of Error in Sampling

Error in sampling is one of the ways that reasoning can be 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 Error in Sampling occurs when a bad data set is chosen, creating a false impression. A sampling error is defined by the differences between the sample and the entire group which the sample is supposed to represent. The sample can be of people's opinions, people's physical condition, people's characteristics, parts coming from an assembly line, plants in the wild, plants on farms, plants on a single farm, or any other thing.

Errors in sampling fallacies can be committed accidentally or purposely for a nefarious purpose. The results of sampling cannot be used to determine truth. It can only result in inductive reasoning. If an attempt to use inductive reasoning as a basis of a premise in deductive reasoning, the deductive reasoning is unsound.

Examples of the Logical Fallacy of Error in Sampling

The Kinsey report is a famous example of error in sampling. Serious Flaws in Kinsey Research: "Kinsey's sample was entirely voluntary and not representative of the U.S. population. White people were overrepresented while Blacks and Latinos were underrepresented. In addition, college students, college graduates, and white-collar workers were overrepresented. Prison inmates comprised 25 percent of Kinsey's male sample, even though they made up less than one percent of the total U.S. population at the time. Among women, 58 percent of Kinsey's sample were unmarried, three times the actual number at the time. Religious people were not adequately represented and since only 10 states were included, the survey was regionally skewed."

This was not the only problem with the Kinsey research. It is sad that the media welcomed the flawed research unquestioningly and the court systems used this flawed research to distort cases that are still defining (corrupting) the U. S. justice system. Serious Flaws in Kinsey Research: "The Kinsey male report contains data on sexual activity of 317 children aged 2 months to 15 years. These data were either manufactured or these children were sexually molested by adults in the name of science." Logical fallacies cause real problems. They can destroy marriages, organizations, churches, denominations, or countries. They are lies. It is the Truth that sets free. Lies bind and destroy.



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Last updated: Sep, 2014
 
 




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Logical Fallacy of Misused Statistics

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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 Generalization

Logical Fallacy of Generalizing from a Hypostatization

Logical Fallacy of Error in Sampling

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