Probability & Statistics

Build statistical intuition through simulation and visualization. Understand distributions, hypothesis testing, and Bayesian reasoning—grounded in real data.

10 modules0 available~12 hours total

About This Course

Probability and statistics are everywhere—from A/B testing to medical trials to machine learning. This course builds your intuition by letting you see the math in action.

Instead of memorizing formulas, you'll generate data, run simulations, and watch distributions emerge. The AI tutor can create synthetic datasets on the fly, helping you understand why the Central Limit Theorem works or why Bayes' Theorem feels counterintuitive.

Inspired by Statistics 110 (Harvard) and Seeing Theory (Brown University).

Prerequisites

  • Basic algebra and arithmetic
  • Familiarity with Python helpful but not required

What You Will Learn

  • Understand probability fundamentals: events, independence, conditional probability
  • Master Bayes' Theorem and apply it to real-world problems
  • Work with common distributions: Normal, Binomial, Poisson
  • Perform hypothesis testing and interpret p-values correctly
  • Develop intuition through simulation and visualization

Your Learning Path

Each module builds on the last. Take your time—the AI tutor is with you at every step.

1

Probability Fundamentals — Events, outcomes, and the rules of chance

40 minComing soon
2

Conditional Probability — How new information changes what we know

40 minComing soon
3

Bayes' Theorem — Updating beliefs with evidence

45 minComing soon
4

Random Variables — From outcomes to numbers

40 minComing soon
5

Common Distributions — Normal, Binomial, Poisson, and friends

50 minComing soon
6

Expected Value and Variance — Measuring center and spread

40 minComing soon
7

The Central Limit Theorem — Why the normal distribution is everywhere

45 minComing soon
8

Hypothesis Testing — Making decisions with data

50 minComing soon
9

Confidence Intervals — Quantifying uncertainty

40 minComing soon
10

Bayesian Inference — A different way to think about probability

50 minComing soon