Relative Frequency

Relative frequency is a type of frequency that compares how often a result occurs to the total number of outcomes.

Relative frequency can be calculated by dividing the number of times an event occurs by the overall number of events or trials.

This measure is used in statistics to give a percentage or probability of an event happening, as opposed to the actual number of times it occurred.

The sum of all relative frequencies for all possible results always equals 1 or 100%, because they represent all the possible outcomes.

For example, if spinning a spinner 20 times results in 5 spins landing on blue, the relative frequency of landing on blue would be 5/20 = 0.25, or 25%.

It is important to remember that as the number of trials or events increases, the relative frequency tends to get closer to the theoretical probability.

Theoretical probability is what you expect to happen, based on all the possible outcomes. It is determined mathematically. On the other hand, relative frequency is based on actual experiments or trials and what actually happened.

Relative frequency can be plotted on a histogram where the horizontal axis represents the outcomes or events and the vertical axis represents their corresponding relative frequencies.

Practical applications of relative frequency can be found in various fields such as science, economics, and weather forecasting.

Tasks involving relative frequency often include determining an estimated probability from an experiment or survey data. This requires counting up occurrences and figuring out the total number of trials.

Understanding relative frequency can help predict outcomes and make informed decisions, whether you’re predicting weather patterns, estimating how a stock will perform, or determining odds in a game.