Table of Contents
Basic Probability and Discrete Probability Distributions
Chapter Objectives
What is Probability?
Methods of Assigning Probability
a priori Classical Method
Empirical Classical Method
Experiments & Outcomes
Outcome Properties
Events
Contingency Table
PPT Slide
Simple (Marginal) Probability
Simple (Marginal) Probability Example
Joint Event Probability
Event Probability Using Contingency Table
Special Events
Joint Event Probability Example
Addition Rule
Addition Rule Example 1: Non-mutually Excl.
Addition Rule Example 2: Mutually Excl.
Conditional Probability
Conditional Probability Example
Conditional Probability Example (Another Approach)
Statistical Independence
Determining Statistical Independence Example
Multiplication Rule
Multiplication Rule Example (Sampling without Replacement)
Multiplication Rule Example (Sampling with Replacement)
Discrete Random Variable and Probability
Discrete Random Variable Probability Distribution
Discrete Random Variable Probability Distribution Example
Expected Value of a Discrete Random Variable
Variance and Standard Deviation of a Discrete Random Variable
Expected Value Example
Variance and Standard Deviation Example
Expected Monetary Value
Expected Monetary Value
Coefficient of Variation
Return-to-Risk Ratio
Binomial Distribution Properties
Binomial Probability Distribution Function
Binomial Probability Distribution Example
Binomial Distribution Characteristics
Conclusion
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Author: Revision: Gerald Clarke Original: John J. McGill
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