References
STAT 350 Handouts
Preface
1
Randomness and Probability
2
Working with Probabilities
3
Probability Models: Outcomes, Events, and Random Variables
4
Probability Models: Probability Measures
5
Introduction to Simulation
6
Marginal Distributions
7
Averages and Standard Deviation
8
Joint Distributions and Correlation
9
Conditioning
10
Conditional Distributions
11
Some Probability Rules
12
Independence
13
Equally Likely Outcomes, Counting Rules, and Uniform Probability Meaures
14
Discrete Random Variables: Probability Mass Functions
15
Continuous Random Variables: Probability Density Functions
16
Cumulative Distribution Functions
17
Quantile Functions
18
Expected Value
19
Variance and Standard Deviation
20
Joint Distributions
21
Covariance and Correlation
22
Expected Values of Linear Combinations of Random Variables
23
Conditional Distributions
24
Conditional Expected Value
25
Binomial and Negative Binomial Distributions
26
Poisson Distributions
27
Normal Distributions
28
Central Limit Theorem
29
Stochastic Processes
30
Mean and Autocorrelation Functions of Stochastic Processes
31
Stationary Stochastic Processes
32
Power Spectral Density
33
Linear Filtering of Stationary Stochastic Processes
34
Gaussian Processes and Brownian Motion
Application: Diagnostic Testing
Application: Probability Rules
Application: Going Nuts with Probability Density Functions
Application: Sketchy Distributions
Application: Major Distributions
Application: Poisson Processes
References
Appendices
Some Problem-Solving Strategies
Summary of Some Common Distributions
References
Application: Poisson Processes
Some Problem-Solving Strategies