MIT · on MIT OpenCourseWare

Statistics for Applications (18.650)

4.8(3,200) on MIT OpenCourseWare·450K enrolled
Intermediate 30 hours EnglishFREE
Our recommendation
MIT's Statistics for Applications, free on OpenCourseWare — a rigorous treatment of the statistical methods used in data science and research, from estimation to regression and Bayesian ideas. It is mathematical and demanding, an excellent foundation with no certificate from the free materials.

Good for: Mathematically comfortable learners who want rigorous applied statistics.

Less suitable if: You want a gentle, applied-only course, or you need a certificate.

Skills you'll gain

StatisticsHypothesis testingRegressionEstimationBayesian statisticsStatistical inference

Is this course right for you?

A good fit if you…

You are comfortable with maths
You want rigorous statistics
You are heading into data science or research

Consider something else if you…

You want a gentle applied course
You are uncomfortable with maths
You need a certificate

Requirements: Calculus and probability; intermediate to advanced.

Realistic time: About 30 hours of lectures, plus practice.

About this course

MIT 18.650 is a graduate-level statistics course covering the mathematical foundations of statistical inference: parameter estimation and maximum likelihood, confidence intervals, hypothesis testing (frequentist and Bayesian), linear and logistic regression, and goodness-of-fit tests. Philippe Rigollet teaches it with full mathematical rigor — proofs, not just formulas — at the pace MIT graduate students experience.

What you'll learn

Apply maximum likelihood estimation to statistical models
Construct and interpret confidence intervals rigorously
Conduct hypothesis tests with formal understanding of Type I/II errors
Understand and implement linear and logistic regression mathematically
Apply Bayesian inference methods and understand their relationship to frequentist approaches

This course includes

30h
On-demand video
Yes
Mobile access
English
Language

What it costs

Completely free through MIT OpenCourseWare. There is no certificate.

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Instructor

PR
Philippe Rigollet
MIT OpenCourseWare instructor
450K+ learners5 courses4.8 instructor rating

Taught by Philippe Rigollet, Professor of Mathematics at MIT, whose research focuses on statistics and machine learning theory.

About this provider

MO
MIT OpenCourseWare
MIT OpenCourseWare — free, openly licensed course materials from MIT's actual courses, including lecture notes, problem sets, and exams. No certificate.
Visit MIT OpenCourseWare

Frequently asked questions

No. OpenCourseWare provides the materials free but does not certify completion.
Completely. All lectures and materials are open.
Yes. It is mathematically rigorous, covering the theory behind statistical methods.
Calculus and probability. It is pitched at intermediate to advanced level.
Khan's is a gentle, applied introduction; MIT 18.650 is rigorous and theory-heavy. Use Khan to build up, then this for depth.
Free
to audit
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