Feb 14 - probability

I've posted my version of the answers to the homework due today.

Discuss conditional probability and Bayes rule. Here are a few sources.

• my attached probability notes
• our textbook, in chapter 6
• my Oct 13 2015 AI notes

If there's time, start discussing hypothesis testing (chap 7 in the text, though I think his discussion of these topics is not the clearest).

Here are a few sources.

• textbook, chapter 7
• wikipedia: statistical hypothesis testing, particularly the "courtroom" analogy
• simple hypothesis testing - video - Khan Academy , and the videos that follow that
• hypothesis testing - examples from a stats course at Duke

I have found many of the explanations of these ideas to be somewhat bewildering. My experience is that it takes examples and working through practice problems on your own to see how this games works.

The terms you want to understand are

• null hypothesis H0
• alternative (motivated) hypothesis H1
• type-1 error
• type-2 error
• p-value

Read about this stuff. We'll do a few examples for Tuesday. I'll come up with an assignment for next Friday

The book also discusses "Bayesian inference" briefly, which I will (briefly) go over - at least the idea - but don't expect to use this semester.

asides

• NSA's python course

attachments

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