STAT 350 - Probability and Random Process MOC
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Follow this guide to see what topics are covered in what sections in the actual textbook. Or you can just peruse the topics:
| File | Section, Subsection |
|---|---|
| Events | 11 Sample Spaces and Events |
| Sample Spaces | 11 Sample Spaces and Events |
| Set Theory Relations in Statistics | 11 Sample Spaces and Events |
| Axioms for Probabilities | 12 Axioms, Interpretations, and Properties of Probability |
| Contingency Tables | 12 Axioms, Interpretations, and Properties of Probability |
| Determining Probabilities Systematically | 12 Axioms, Interpretations, and Properties of Probability |
| Equally Likely Outcomes | 12 Axioms, Interpretations, and Properties of Probability |
| Relative Frequency | 12 Axioms, Interpretations, and Properties of Probability |
| Rules and Properties of Probability | 12 Axioms, Interpretations, and Properties of Probability |
| Definition of Conditional Probability | 21 Conditional Probability |
| Multiplication Rule for Conjunct | 21 Conditional Probability |
| Bayes' Theorem | 22 The Law of Total Probability and Bayes' Theorem |
| Partition | 22 The Law of Total Probability and Bayes' Theorem |
| The Law of Total Probability | 22 The Law of Total Probability and Bayes' Theorem |
| Independence in Probability | 23 Independence |
| Independence of More Than 2 Events | 23 Independence |
| Multiplication Rule for Independent Events | 23 Independence |
| Random Variables | 31 Random Variables |
| Two Types of Random Variables - Discretes vs. Continuous | 31 Random Variables |
| Probability Distribution, PMF | 32 Probability Distributions for Discrete Random Variables |
| Expected Value | 34 Expected Value and Standard Deviation |
| Variance and Standard Deviation of X | 34 Expected Value and Standard Deviation |
| Parameters and Families of Distributions | 41 Parameters and Families of Distributions |
| Binomial Experiment | 42 The Binomial Distribution |
| The Binomial Random Variable and Distribution | 42 The Binomial Distribution |
| Poisson Distribution | 43 The Poisson Distribution |
| Geometric Distribution | 45 Negative Binomial Distribution |
| Negative Binomial | 45 Negative Binomial Distribution |
| Probability Distributions for Continuous Variables (PDF) | 51 Continuous Random Variables and Probability Density Functions |
| Cumulative Distribution Function (CDF) | 52 The Cumulative Distribution Function and Percentiles |
| Obtaining PDF from CDF (f to F) | 52 The Cumulative Distribution Function and Percentiles |
| Percentiles of a Continuous Distribution | 52 The Cumulative Distribution Function and Percentiles |
| Expected Values (Continuous Case) | 53 Expected Values, Variance |
| Properties of Expectation and Variance (continuous version) | 53 Expected Values, Variance |
| Variance (Continuous Version) | 53 Expected Values, Variance |
| Arbitrary Normal Distributions | 61 Normal (Gaussian) Distribution |
| Gaussian (Normal) Distribution | 61 Normal (Gaussian) Distribution |
| Standard Normal Distribution | 61 Normal (Gaussian) Distribution |
| Exponential Distribution | 63 Exponential Distribution |
| Independent Random Variables | 71 Joint Distributions for Discrete Random Variables |
| Joint Probability Mass Function (JPMF) | 71 Joint Distributions for Discrete Random Variables |
| Independence of Continuous Random Variables | 72 Joint Distributions for Continuous Random Variables |
| Marginal Probability Density Functions | 72 Joint Distributions for Continuous Random Variables |
| The Joint Probability Density Function for Two Continuous Random Variables | 72 Joint Distributions for Continuous Random Variables |
| Correlation | 73 Expected Values, Covariance, and Correlation |
| Covariance | 73 Expected Values, Covariance, and Correlation |
| Expected Value (Joint) | 73 Expected Values, Covariance, and Correlation |
Lecture notes are done via handouts from class, which won't show up on the site (if you're viewing this through it). They'll be described in the following TOC:
| File | Type |
|---|---|
| Lecture 1 - Sample Spaces | Lecture Notes |
| Lecture 10 - Continuous Probabilities | Lecture Notes |
| Lecture 11 - More on Continuous Distributions | Lecture Notes |
| Lecture 2 - cont. Basic Probability | Lecture Notes |
| Lecture 3 - Starting Conditional Probability | Lecture Notes |
| Lecture 4 - More on Conditional Probability | Lecture Notes |
| Lecture 5 - Finishing Independence | Lecture Notes |
| Lecture 6 - Bayes' Rule | Lecture Notes |
| Lecture 7 - More on Mean, Std Dev | Lecture Notes |
| Lecture 8 - Discrete Models | Lecture Notes |
| Lecture 9 - Poisson Distribution | Lecture Notes |