# Probability Tutorial

Applied researchers make decisions under uncertainty. Probability theory makes it possible for researchers to quantify the extent of uncertainty inherent in their conclusions and inferences.

This tutorial covers the essence of probabilty theory clearly and simply in just a few short lessons. The tutorial focuses on six topics:

• Probability basics. To solve probability problems, it helps to know about sets, subsets, and statistical experiments.
• Probability problems. To solve probability problems, you need to understand the rules of probability; and you need to know how to count data points.
• Poker probability. To compute probabilities for poker hands, you rely on fundamental principles in probability. It's a great way to build analytical skill, and it's fun.
• Random variables. Random variables are at the heart of probability. They can be characterized by central tendency, variability, and a probability distribution.
• Discrete probability distributions. How to work with binomial, hypergeometric, multinomial, negative binomial, and Poisson distributions.
• Continuous probability distributions. How to work with normal, standard normal, chi-square, t-, and f-distributions.

This tutorial is designed for students and researchers who have some familiarity with introductory statistics (e.g., a high school statistics course or Advanced Placement Statistics).

### How to Use This Tutorial

Individual lessons are accessible through the table of contents, which can be found in the vertical column on the left side of the page. You should work through lessons in the order in which they appear; because some lessons build on previous lessons.

Individual lessons are accessible through the table of contents, which can be accessed by tapping the "Probability: Table of Contents" button at the top of the page. You should work through lessons in the order in which they appear; because some lessons build on previous lessons.