Seeing Theory

A visual introduction to probability and statistics.

Chapter 1

Basic Probability

This chapter is an introduction to the basic concepts of probability theory.

Go to Basic Probability

Chapter 2

Compound Probability

This chapter discusses further concepts that lie at the core of probability theory.

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Conditional Probability

Chapter 3

Probability Distributions

A probability distribution specifies the relative likelihoods of all possible outcomes.

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Random Variables

Discrete and Continuous

Central Limit Theorem

Chapter 4

Frequentist Inference

Frequentist inference is the process of determining properties of an underlying distribution via the observation of data.

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Point Estimation

Interval Estimation

Chapter 5

Bayesian Inference

Bayesian inference techniques specify how one should update one’s beliefs upon observing data.

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Prior to Posterior

Chapter 6

Regression Analysis

Regression Analysis is an approach for modeling the linear relationship between two variables.

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Ordinary Least Square

Analysis of Variance

Seeing Theory was created by Daniel Kunin while an undergraduate at Brown University. The goal of this website is to make statistics more accessible through interactive visualizations (designed using Mike Bostock’s JavaScript library D3.js).

The Team

Daniel
Kunin

Jingru
Guo

Tyler
Dae Devlin

Daniel
Xiang

Awards & Press

We are currently working on a textbook for Seeing Theory. Download a draft of our pdf below. You can provide feedback on our writing here.