Kolmogorov’s Inequality in statistics is a theorem that states that any two probability distributions (i.e. collections of data) are not always equal. In other words, some variables may be more likely to appear in one distribution compared to another.
This inequality can sometimes lead to surprising conclusions about how the data behaves.
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