AP Statistics is an examination by the CollegeBoard.

See also crap to remember for AP Stats

Non-Focus Mistakes

• file:///Users/houliu/Documents/School Work/The Bible/APStats/APStats5Steps.pdf
• file:///Users/houliu/Documents/School Work/The Bible/APStats/APStats5Steps.pdf
• file:///Users/houliu/Documents/School Work/The Bible/APStats/APStats5Steps.pdf
• Interpretation of regression outputs

Backlog

• Chi-square
• file:///Users/houliu/Documents/School Work/The Bible/APStats/APStats5Steps.pdf
• file:///Users/houliu/Documents/School Work/The Bible/APStats/APStats5Steps.pdf

Notes

• confidence interval
• hypothesis testing
• t-statistics
• chi-square
• data inference
• binomial distribution

Exploring CLRS.

2

• insertion sort

Notes on CS 107, C, MIPS, and computational systems.

Lectures

• SU-CS107 SEP272023
• SU-CS107 SEP292023
• SU-CS107 OCT022023
• SU-CS107 OCT032023
• SU-CS107 OCT042023
• SU-CS107 OCT062023
• SU-CS107 OCT092023
• SU-CS107 OCT112023
• SU-CS107 OCT132023
• SU-CS107 OCT182023
• SU-CS107 OCT202023
• SU-CS107 OCT232023
• SU-CS107 OCT252023
• SU-CS107 OCT272023
• SU-CS107 NOV102023
• SU-CS107 NOV132023
• SU-CS107 DEC012023

Worksheets

• SU-CS107 Midterm Sheet

What random variable should I use?

Unit 1

core probability, axiom of probability, counting, combination, permutation, DeMorgan’s Law.

• SU-CS109 SEP272023
• SU-CS109 SEP292023
• SU-CS109 OCT022023
• SU-CS109 OCT042023
• SU-CS109 OCT062023
• SU-CS109 OCT112023

Unit 2

random variables

• SU-CS109 OCT092023
• SU-CS109 OCT132023
• SU-CS109 OCT162023
• SU-CS109 OCT182023

Unit 3

inference, General Inference

• SU-CS109 OCT202023
• SU-CS109 OCT232023
• SU-CS109 OCT252023
• SU-CS109 OCT272023

Unit 4

Beta Distribution, central limit theorem, bootstrapping

• SU-CS109 NOV012023
• SU-CS109 NOV032023
• SU-CS109 NOV102023

Unit 5

Apredezahe de machinas: Naive Bayes, logistic regression, deep learning

• SU-CS109 NOV132023
• SU-CS109 NOV292023
• SU-CS109 DEC012023
• SU-CS109 DEC042023

Notes

• SU-CS109 Midterm
• SU-CS109 Midterm Sheet

Lecture notes taking during CS238, decision making. Stanford Intelligence Systems Laboratory (SISL: planning and validation of intelligent systems).

Big Ideas

Themes

1. There’s a principled mathematical framework for defining rational behavior
2. There are computational techniques that could lead to better, and perhaps counter-intuitive decisions
3. Successful application depends on your choice of representation and approximation
   • you typically can’t solve mathematical models exactly
   • so, we have to rely on good models of approximations
4. The same computational approaches can be applied to different application domains
   • the same set of abstractions can be carried through life
   • send Mykel a note about how these topics about where this stuff is applied

These algorithms drive high quality decisions on a tight timeline. You can’t fuck up: people die.