Dependent Events In Probability Theory: A Comprehensive Guide

Dependent Event

When one event does have an effect on the another event

A dependent event is an event in which the outcome of one event is influenced by the outcome of another event. In other words, the probability of the second event occurring is dependent on the outcome of the first event.

To illustrate this, let’s say we are drawing cards from a deck of 52 cards without replacement. If we draw a card and do not replace it back in the deck, the probability of the second card being drawn is influenced by which card was drawn first. For example, if the first card drawn was a King of Hearts, the probability of drawing another King of Hearts in the second draw decreases because there are now fewer King of Hearts remaining in the deck.

Another example of a dependent event is rolling two dice. If we roll one die and it lands on a 4, the probability of rolling a total of 7 on two dice decreases because we already know that one die landed on a 4.

Dependent events are important in probability theory and real-life scenarios as they can help us calculate the likelihood of certain outcomes and make more informed decisions.

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