Believing that a coin is more likely to land on "tails" because it has landed on "heads" for the last four tosses is an example of
A) confirmation bias.
B) hindsight bias.
C) the anchoring effect.
D) the gambler's fallacy.

Question

Quizplus · Accepted Answer

This is the gambler's fallacy, the belief that the outcome of a random event is more likely to occur because it hasn't happened in a while, when in reality each toss of the coin is independent of previous tosses and the probability of getting "tails" is still 50%.

Believing That a Coin Is More Likely to Land on "Tails