# Empirical Probability Examples

### Introduction to Empirical Probability

An empirical probability (also called experimental probability) is calculated by collecting data from past trials of the experiments. The experimental probability obtained is used to predict the future likelihood of the event occurring.

### Formula and Examples of Empirical Probability

To calculate an empirical/ experimetnal probability, one can use the formula

$$P(A)=\frac{\text{Number of trials in which A occurs} }{\text{Total number of trials}}$$

### Key Points about Empirical Probability

• It is based on actual data, not theoretical models.
• It is a good approach when the data is from similar events in the past.
• The more data you have, the more accurate the estimate will be.
• It is not always perfect, as past results do not guarantee future outcomes.

### Empirical Probability also has Limitations

• It can be time-consuming and expensive to collect enough data.
• It may not be representative of the future, especially if the underlying conditions change.

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