Conditional independence

Conditional independence is a concept in probability and statistics that describes a situation where two events are independent of each other when a third event is known. In simpler terms, if you know the outcome of the third event, the results of the first two events don't influence each other. For example, if you know that it is raining, the likelihood of someone carrying an umbrella and someone getting wet are independent events; knowing it’s raining doesn’t change their relationship under that condition. This concept is crucial in fields like statistics, machine learning, and decision-making, helping to simplify complex relationships.