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Gambler's Fallacy

 

Disciplines Argument > Fallacies > Gambler's Fallacy

Description | Discussion | Example | See also

 

Description

Chance is affected by more than random events. It can be controlled by luck, skill and specific identified events. When you hit a 'lucky' patch, you just cannot lose. When the odds are stacked against you, you have no chance.

Example

I've lost three nights in a row. I will win big tonight. I'm wearing my lucky watch, just to make sure.

You know, every time it rains, I've come out without an umbrella and am miles from the car.

Discussion

One of our basic needs is for a sense of control, which we gain by seeking to predict the future and by attributing cause to events that occur. We also seek to win and avoid failure, which further drives us both to explain our losses outside ourselves and also to compensate for losses by trying to end up as a winner.

Habitual gamblers fall headlong into these traps. Many others are affected by it too. For example, 'Murphy's Law' (that when something goes wrong it will be the worst thing at the worst time) is often used to explain and provide comfort when things go wrong. Particularly for the gambler, it also means explaining winnings through external events and lucky charms (most of us prefer to explain winning through personal skills, although where chance is involved, we also fall into the trap). 'Luck' itself is an example, as it does not exist. What is random is random. The laws of statistics are all there are.

When things do go wrong and when our predictions fail, we need to be comforted in some way and the Gambler's Fallacy can be turned to this purpose also. We can explain failures as bad luck rather than incompetence or poor decision-making. We can take comfort in the fact that lady luck has gone out for the evening and there was nothing we could have done to change things.

Classification

Statistical

See also

Gambler's Fallacy (theory), Post Hoc, Attribution Theory, Fundamental Attribution Error

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