(a.k.a. Lying with Statistics, Statistical Fallacy, Misused Statistics, or Statistical Fallacy)
The use of statistics in ways that blur the distinction between reality and make-believe
Rather than using reason to evaluate the issue, persuaders abuse statistics to assert a falsehood. Here’s a partial list of fallacies that abuse statistics:
- Small Sample Size Bias
- Avoiding Specific Numbers
- Bad Statistical Data
- Base Rate Fallacy
- Bayes’ Theorem Fallacy
- Biased Method
- Clustering Illusion
- Error in Sampling
- Fake Precision
- Ludic Fallacy
- Gamblers Fallacy
- Hasty Generalization
- False Precision
- Biased Statistics
One way we can abuse statistics is by implying that statistics are something more than inductive reasoning when the statistical methods use induction rather than deduction. We’re foolish when we get dogmatic about induced conclusions or imply that such inductive reasoning is concrete or definitive.
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