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This course is a part in a series of courses that covers a complete course in probability theory taught in the US colleges.
If you take this course, you can count on my help. I will answer every single question you post on the discussion board.
If you are looking for an efficient way to learn notions of probability theory, I guarantee that this course is for you. In fact, I offer a 30 day money back guarantee.
In this course you will learn conditional probability, Bayes formula, and you will learn how to tell whether two (or more) events are independent or not. The notions of conditional probability and independence are at the heart of probability theory.
The course consists of
In general, practice lectures are marked as easy, intermediate and advanced. All lectures are accompanied with downloadable transcripts.
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|Section 1: Start Here|
|Section 2: Conditional probability|
Conditional probability: MotivationsPreview
Conditional probability: DefinitionPreview
Problem solving (easy)
Problem solving (intermediate)
|Section 3: Bayes Law|
Bayes Law: Motivation and theory
Problem solving (easy): Flu problem
Problem solving (intermediate I)
Problem solving (intermediate II)
|Section 4: Independent events|
Independent events: Motivations
Independent events: Definition
Problems solving (easy)
Problems solving (warning!)
Independence of three events
Independence of more than two events
|Section 5: Thank you!|
I am a professional mathematician. As a mathematician I worked in US, Mexico, Japan, Canada and Germany. I am an author of 16 research papers published in internationally renowned journals.
I taught courses ranging from middle school to PhD level, including such high level courses as Topological Quantum Field Theory, Moduli spaces of Riemann curves, and Topological Surgery Theory.
What you may expect from me is a well structured course with clearly explained notions and theory.