Who is this class for: This course is for people interested in learning an alternative to the Frequentist approach that is typically taught in statistics classes. The course covers both concepts and basic computing, and so it is applicable both to people doing data analysis as well as people who read the analysis of others, such as decision makers. This course expects that learners have previous exposure to statistics at the introductory level or higher, and previous exposure to calculus. In both cases, the expectation is that concepts have been seen previously, possibly many years earlier, but that the details may have been forgotten.


Created by:  University of California, Santa Cruz

  • Herbert Lee

    Taught by:  Herbert Lee, Professor

    Applied Mathematics and Statistics
LevelIntermediate
CommitmentFour weeks of study, two-five hours/week depending on your familiarity with mathematical statistics.
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

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Certificates

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Creators
University of California, Santa Cruz
UC Santa Cruz is an outstanding public research university with a deep commitment to undergraduate education. It’s a place that connects people and programs in unexpected ways while providing unparalleled opportunities for students to learn through hands-on experience.
Ratings and Reviews
Rated 4.5 out of 5 of 477 ratings

This was a great introduction to bayesian statistic. I have background in Computer Science and Engineering but I have not yet been introduced to Bayesian Statistics. The Quizzes were where the learning was happening for me. Personally I learn the best when I code things up. I wish they had also included coding examples in Python (which is what I used for the quizzes) since that is one on the most popular languages for data science.

An interesting introduction to Bayesian statistics and inference. Not for people with no statistical background, as it does assume you are comfortable with various distributions, expectations, variances, etc. and the 'standard' frequentist worldview (including inferential procedures such as linear regression). The material was well explained, and generally well examined, with a mixture of multiple choice understanding questions, and numeric response tasks which also serve as a very basic introduction to R (or Excel if you are crazy). It was good to see the instructor realising that a light shirt was causing problems and switching to a darker one as the videos went on!

Like the course. Learnt a lot. Was able to apply in real world.

Going to week 3, very interesting course, also very interesting cuestions in the quizzes and specially the honor quizzes that make you think....