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In statistics a confounding variable is one which can give rise to spurious correlations. For example, my age is fairly well correlated with the number of television sets in the UK. This is not because my getting older sells more TV sets, nor is it because the sale of TV sets makes me grow older. The real reason is that both these are correlated with time and, as the years pass, both increase. So, time is the confounding variable which gives rise to an apparent relationship between TV sets and my age.

Confounding variables can have serious effects when statistical methods are being used to develop a cause-and-effect model. In truth, there may be no direct causal relationship, only two independent relationships with a third variable - the confounding factor.

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