Mutual information measures how much more is known about one random value when given another. For example, knowing the temperature of a random day of the year will not reveal what month it is, but it will give some "hint". In the same way, knowing what month it is will not reveal the exact temperature, but will make certain temperatures "more or less likely". These "hints" or "changes in likelihood" are explained and measured with mutual information.