In probability theory, empirical probability is an estimated probability based upon previous evidence or experimental results. As such, empirical probability is sometimes referred to as experimental probability, and we can distinguish it from probabilities calculated from a clearly-defined sample space. Let’s first compare and contrast empirical probability and theoretical probability. Then we’ll look at an […]

# Author Archive | Paul King

## Understanding Binomial Probability Distribution

The binomial distribution describes random variables with only two possible outcomes. This post explains the binomial distribution, and how to use it!

## Complementary Events: Definition and Examples

In this post, we use fully worked examples to explain what complementary events are, and how they are related to each other in probability theory.

## Understanding Normal Distribution

The normal distribution, or bell curve, has wide applications in inferential statistics. This post will help you understand what it is, and how to use it!

## What are independent events?

In probability, independence refers to two events that have no impact on one another, like subsequent flips of a coin. Learn more about independence here!

## Mutually Exclusive Events: Definition and Examples

Mutually exclusive events are events that cannot occur at the same time. This post gives numerous examples and practice problems to help you identify them!

## What is inferential statistics?

What is inferential statistics? In this post, learn the difference between descriptive and inferential statistics, and when and how to apply them!