Master The Complement Rule In Probability Theory: The Basics

Complement Rule

P(AC)= 1 – P(A) (C is ^^) also (A’)

The complement rule states that the probability of an event occurring is equal to one minus the probability of that event not occurring. In other words, it is the probability of the opposite of the event.

For example, if the probability of getting heads on a fair coin is 0.5, then the probability of getting tails is also 0.5 (since there are only two possible outcomes). Therefore, the complement probability of getting heads is 1-0.5 = 0.5.

This can also be expressed as P(A) + P(A’) = 1, where A is the event of interest and A’ is the complement (not A).

The complement rule can be useful in situations where it may be easier to calculate the probability of the complement event rather than the event itself. It can also be used to check that probabilities add up to 1 in a given situation.

Overall, the complement rule is an important concept in probability theory that helps to calculate the probability of events and can be used in various real-world applications.

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