Statistics is the science of analyzing data, and in this lesson, you'll learn the basics! Discuss statistical modeling and parameterizing models, too.

In this lesson, discover the building blocks of probability, including random variables, set notation, and two important rules for calculating probabilities.

There are two main types of random variables: discrete and continuous. In this lesson on foundational concepts in statistics and probability, see how they work!

Discover the Strong Law of Large Numbers, discrete random variables, and learn how to calculate variance in this lesson on statistics and probability.

Conditional probabilities add extra information to random variables. They're calculated using the conditional probability formula and Bayes' Rule, covered here.

The Central Limit Theorem says that the sum of random variables tends to look like a normal distribution. Use this to approximate probabilities in this lesson!

This statistics lesson covers the two most important point estimators: the sample average for the mean, and the population variance for the variance.

This lesson covers the idea of the p-value, which is a numerical way of characterizing the evidence against a particular hypothesis with a test statistic.

Confidence intervals contain all numbers between a and b, and can be calculated with the Central Limit Theorem, which is covered in this statistics lesson!

Bayesian statistics treats the parameters as if they are random variables. In this stats lesson, use Bayes' Rule to update the distribution of the parameters.