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The fallacy arises from an erroneous conceptualization of the law of large numbers. For example, "I've flipped heads with this coin five times consecutively, so the chance of tails coming out on the sixth flip is much greater than heads." [66]
The continuum between the extremes is ignored. The term probability neglect was coined by Cass Sunstein. [1] There are many related ways in which people violate the normative rules of decision making with regard to probability including the hindsight bias, the neglect of prior base rates effect, and the gambler's fallacy. However, this bias is ...
Extension neglect [a] is a type of cognitive bias which occurs when the sample size is ignored when its determination is relevant. [1] For instance, when reading an article about a scientific study, extension neglect occurs when the reader ignores the number of people involved in the study (sample size) but still makes inferences about a population based on the sample.
A majority chose answer (b). Independent of the information given about Linda, though, the more restrictive answer (b) is under any circumstance statistically less likely than answer (a). This is an example of the "conjunction fallacy". Tversky and Kahneman argued that respondents chose (b) because it seemed more "representative" or typical of ...
Argument from fallacy (also known as the fallacy fallacy) – the assumption that, if a particular argument for a "conclusion" is fallacious, then the conclusion by itself is false. [ 5 ] Base rate fallacy – making a probability judgment based on conditional probabilities , without taking into account the effect of prior probabilities .
Several theories predict the fundamental attribution error, and thus both compete to explain it, and can be falsified if it does not occur. Some examples include: Just-world fallacy. The belief that people get what they deserve and deserve what they get, the concept of which was first theorized by Melvin J. Lerner in 1977. [11]
The gambler's fallacy, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the belief that, if an event (whose occurrences are independent and identically distributed) has occurred less frequently than expected, it is more likely to happen again in the future (or vice versa).
In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy. The consequences of such misinterpretations can be quite severe. For example, in medical science, correcting a falsehood may take decades and cost lives. Misuses can be easy to ...