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By the end you can write down the sample space of a simple random experiment, count the outcomes that belong to an event, and use those counts to find a probability, including the probability that the event does not happen.
Probability is a number from to that measures how likely an event is.
An event with probability cannot happen. An event with probability is certain. Everything in between is a matter of degree, and means "just as likely to happen as not".
To compute a probability we need a precise description of what could happen. That description is the sample space.
Sample space
An experiment is anything with an uncertain result, such as rolling a die. Each time you do it is called a trial.
The sample space, usually written , is the set of all possible outcomes of the experiment.
Set notation. Curly brackets mean "the set containing". For one roll of a die, , and the event "roll an even number" is .
Suppose the experiment has finitely many outcomes and they are all equally likely. Then, for any event ,
The logic is that probability is shared out evenly between the equally likely outcomes, so each one gets where is the size of . An event made of outcomes collects of those shares.
The equally likely condition is essential. This formula fails if the outcomes are not equally likely. Rolling two dice and adding the scores is the classic trap: the sums to are not equally likely, even though the two dice are fair.
Worked example: Example 1: counting a total
Two fair six-sided dice are rolled and the two scores are added. Find the probability that the total is .