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Contents
- 1 Axioms of probability (finite spaces, infinite spaces)
- 2 Sequential and continuous probability models
- 3 Properties of probability laws
- 4 Conditional probability
- 5 Independence
- 6 Conditional Independence
- 7 Random Variables
- 8 Probability mass functions
- 9 Common random variables (Bernoulli, binomial, geometric) and how they come about
- 10 Functions of random variables
- 11 Mean and Variance, and their properties
- 12 Joint PMFs of more than one random variable
Axioms of probability (finite spaces, infinite spaces)
$ P(A) \geq 0 $ for all events A
Sequential and continuous probability models
Properties of probability laws
Conditional probability
Independence
Conditional Independence
Random Variables
Probability mass functions
Common random variables (Bernoulli, binomial, geometric) and how they come about
Functions of random variables
Mean and Variance, and their properties
$ E[X] = \sum_x x p_X(x) $
