Let’s begin with three concepts at the foundation of probability theory:
Probability deals with what statisticians call random experiments, also known as statistical experiments. A random experiment is a process whose outcome cannot be predicted with certainty.
For example, before tossing a coin or rolling a die, you can’t know the result of the toss or the roll. The result of the coin toss might be heads or tails. The result of the die roll might be 3 or 6.
All random experiments have three things in common:
In statistics, the result of a random experiment is called an outcome. For example, if you roll a die, there are six possible outcomes: 1, 2, 3, 4, 5, 6.
An event is a set of one or more outcomes. Using the example of rolling a die, an event might be rolling an even number. The event of rolling an even number consists of the outcomes 2, 4, 6. Or, the event of rolling an odd number consists of the outcomes 1, 3, 5.
In a random experiment, an event is assigned a probability. Let’s explore how to represent and calculate the probability of a random event.
The probability that an event will occur is expressed as a number between 0 and 1. Probability can also be expressed as a percent.