What is it?
The gambler's fallacy occurs when someone believes that past random events affect the probability of future random events, even though the events are statistically independent. It assumes that random processes will 'even out' or 'correct themselves' over time.
Examples
Person A: 'The roulette wheel has landed on black five times in a row, so red is due to come up next.'
Person B: 'I've applied for ten jobs without success, so I'm bound to get the next one.'
How to Avoid This
Remember that truly random events have no memory of past outcomes. Each independent event has the same probability regardless of what happened before.
How to Counter This
Explain the independence of random events: 'Each spin/flip/draw is an independent event with the same probability. Past outcomes don't influence future probabilities in truly random processes.'