Core

Specializations

Probability & Statistics

Probability & Statistics Courses

Prerequisites: High school algebra.

- Harvard's course is the best course to take if you want to gain a comprehensive understanding of introductory probability and statistics.
- If you want to dive deeper into the foundations of probability, MIT 6.012 is a nice complement.
- If you haven't had a math course in a long time or think the Harvard or MIT courses are too hard, Khan Academy's modules are a great introduction as well.
- MIT 18.650 is more suitable for people who already had an introduction to probability and statistics.

Course

Year

Description

Difficulty Level

Resources

2013

Overall the best introduction course to probabil**i**ty and statistics. The combination of lectures, problem sets and the free textbook will give you a comprehensive overview from the ground up.

Medium

2018

This course goes through a lot of the probability theory topics of the above course in a bit more depth and provides more step-by-step guidance, e.g. by reviewing set theory.

Medium

2014

The most approachable course on the topic. In typical Khan Academy fashion, it equips the learner with a broad overview of the topic by providing simple explanations and insightful examples.

Easy

2016

This course is suitable for anyone who already has some basic understanding of probability and statistics. It goes through applications of statistics such as parametric inference, principal component analysis and generalized linear models.

Medium

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Resource

Year

Description

Type

2019

A rigorous introduction to probability theory that reflects and extends the content covered in the Harvard Stats 110 course.

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2019

Doesn't cover a lot of probability theory, but goes through statistics topics such as summarizing data, inference and linear regression in a very approachable manner. Includes chapter videos and coding labs.

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2018

One of the most beautiful visualizations and explanations of probability and statistics. Also links to a free draft of a textbook.

π π

Continuously updated

Approachable videos to topics such as multicollinearity, autocorrelation or probability distribution functions.

π₯

Continuously updated

Videos focused on Regression, ANOVA, Hypothesis Testing etc.

π₯

2015

Videos covering the basics of Statistics & Probability from Random Variables to Markov chains.

π₯

β

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