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Cherry picking, suppressing evidence, or the fallacy of incomplete evidence is the act of pointing to individual cases or data that seem to confirm a particular position while ignoring a significant portion of related and similar cases or data that may contradict that position. Cherry picking may be committed intentionally or unintentionally.
Argument from anecdote – a fallacy where anecdotal evidence is presented as an argument; without any other contributory evidence or reasoning. Inductive fallacy – a more general name for a class of fallacies, including hasty generalization and its relatives. A fallacy of induction happens when a conclusion is drawn from premises that only ...
The fallacy of suppressed correlative is a type of argument that tries to redefine a correlative (one of two mutually exclusive options) so that one alternative encompasses the other, i.e. making one alternative impossible. [1] This has also been known as the fallacy of lost contrast [2] and the fallacy of the suppressed relative. [3]
False evidence, fabricated evidence, forged evidence, fake evidence or tainted evidence is information created or obtained illegally in order to sway the verdict in a court case. Falsified evidence could be created by either side in a case (including the police/ prosecution in a criminal case ), or by someone sympathetic to either side.
Exploring a forking decision-tree while analyzing data was at one point grouped with the multiple comparisons problem as an example of poor statistical method. However Gelman and Loken demonstrated [2] that this can happen implicitly by researchers aware of best practices who only make a single comparison and only evaluate their data once.
Confounding is defined in terms of the data generating model. Let X be some independent variable, and Y some dependent variable.To estimate the effect of X on Y, the statistician must suppress the effects of extraneous variables that influence both X and Y.
As with any logical fallacy, identifying that the reasoning behind an argument is flawed does not necessarily imply that the resulting conclusion is false. Statistical methods have been proposed that use correlation as the basis for hypothesis tests for causality, including the Granger causality test and convergent cross mapping.
For example, confirmation bias produces systematic errors in scientific research based on inductive reasoning (the gradual accumulation of supportive evidence). Similarly, a police detective may identify a suspect early in an investigation, but then may only seek confirming rather than disconfirming evidence.