STAT 350 Handouts

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

Table of contents

Preface

STAT 350 Handouts

Author

Kevin Ross

Published

Mar 10, 2023

Preface

Handouts containing examples, exercises, and notes covering selected topics from Cal Poly STAT 350.

1 Randomness and Probability