Gambler’s fallacy is a unique psychological blockage in the interpretation of statistical events. Suppose we have thrown a coin up ten times and got head each time, we feel as if tail is due next time but actually speaking probability is only 50%. This is gambler’s fallacy or Monte Carlo Fallacy. Likewise, if a batsman has failed 7 times, the manager thinks he is due to succed next time. Truly Speaking his probability speaking of success is 50% but manager assign him a higher responsibility.
On August 18, 1913, at the casino in Monte Carlo, black came up a record twenty-six times in succession [in roulette]. Next, there was a near-panicky rush to bet on red. By this time black had come up a phenomenal fifteen times. In application of the the gambler’s fallacy, players doubled and tripled their stakes on red. This doctrine leading them to believe after black came up the twentieth time that there was not a chance in a million of another repeat. In the end the unusual run enriched the Casino by some millions of francs. The term got coined as Monte Carlo Fallacy or gambler’s fallacy.
Gamble’s fallacy is complete inability to understand the statistical independence. i.e occurrence of one statistical even has no influence on the chance of occurrence of another.
When we use the heuristic of representativeness to arrive at subjective probabilities, we decide first whether the current situation is similar to one we have encountered before and then we act accordingly. In other words, we ask whether the current situation is a representation, or instance of something we have already experienced. This method can work, but it may result in our being misled by surface similarities. It is also possible that the original situation, the one that serves as basis for comparison may not be a representative of the true state of affairs. In making a decision on the basis of representativeness, the individual may also be a victim of gambler’s fallacy.