Chapter 15 Probability

Chapter 15 Probability

15.1 What is Probability

15.1.1 Events and Probability

Events
Probability

Two types:
frequentlist or classical
Bayesian

See also: Likelihood: http://students.brown.edu/seeing-theory/basic-probability/index.html#first
Expectation: http://students.brown.edu/seeing-theory/basic-probability/index.html#second
and Estimation: http://students.brown.edu/seeing-theory/basic-probability/index.html#third

When two events are said to be independent of each other, what this means is that the probability that one event occurs in no way affects the probability of the other event occurring. An example of two independent events is as follows; say you rolled a die and flipped a coin.

15.1.2 Conditional Probability

15.1.3 Intersection

15.1.4 Union

15.1.5 Complement

See Also:
Set Theory: http://students.brown.edu/seeing-theory/compound-probability/index.html#first
Combinatorics: http://students.brown.edu/seeing-theory/compound-probability/index.html#second
Conditional Probability: http://students.brown.edu/seeing-theory/compound-probability/index.html#third

Random Variables and Probability Distributions

15.2.1 Realizations

15.2.2 Discrete Random Variables

cumulative probability distributions of discrete random variables. Mean and Variance of a discrete random variable

15.2.3 Continuous Random Variables

Cummulative Probability distributions of continuous Random Variables Mean and Variance of a Continuous Random Variable

15.2.4 Shape, Skew and Modality