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Flashcards in Statistical fallacies Deck (7)
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We think that statistically independent events are related when they are not
e.g. likelihood of flipping heads if just got tails

The Gambler's Fallacy


Just because two variables vary together does not mean that one caused the other (no causal connection)

Mistaking correlation for causation fallacy


Conjunction fallacy

Thinking that the conjunction of two events is more likely than a single general event
Higher probability of A occurring than A and B (as A*B < A, unless A = 1/is definite)


Mistaking statistical significance for clinical significance

Finding statistical significance does not mean that the thing is clinically significant
A significant statistical difference between two variables means that it was likely not due to chance, not necessarily that the treatment was clinically effective.
e.g. 3% difference between two things may not have any significant effect clinically


Base rate fallacy (not common, very specific)

If presented with base rate information (general information) and information about a specific case, we tend to ignore the general information and only focus on the specific case.


Truth inflation (not fallacy)

Made up of
File drawer effect: researchers who don't find any effect just put their work away and never submit it for publication
Publication bias: research reporting that there is some effect is far more likely to be published than research that shows there is no effect (as more interesting)

Thus, much higher probability that a statistically significant event reported in a published study was just due to random chance (not seeing negatives, resulting in lots of false positives).


Regression to the mean (not fallacy)

outliers are more likely to come back/regress to the mean because it is more likely to gather around the mean as it is the most common (and that mean will move closer to the outlier)