b.lect10

# b.lect10 - Outline Some Common Discrete Distributions...

This preview shows pages 1–9. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Outline Some Common Discrete Distributions Lecture 10 Chapter 3: Random Variables and Their Distributions Michael Akritas Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable I A r.v. X is called Bernoulli if it takes only two values. Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable I A r.v. X is called Bernoulli if it takes only two values. I The two values are referred to as success (S) and failure (F), or are re-coded as 1 and 0. Thus, always, S X = { , 1 } . Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable I A r.v. X is called Bernoulli if it takes only two values. I The two values are referred to as success (S) and failure (F), or are re-coded as 1 and 0. Thus, always, S X = { , 1 } . I Experiments resulting in a Bernoulli r.v. are called Bernoulli . Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable I A r.v. X is called Bernoulli if it takes only two values. I The two values are referred to as success (S) and failure (F), or are re-coded as 1 and 0. Thus, always, S X = { , 1 } . I Experiments resulting in a Bernoulli r.v. are called Bernoulli . Example 1. A product is inspected. Set X = 1 if defective, X = 0 if non-defective. Michael Akritas Lecture 10 Chapter 3: Random Variables and Their Distribution Outline Some Common Discrete Distributions The Bernoulli Random Variable The Binomial Random Variable The Hypergeometric Random Variable The Negative Binomial Random Variable I A r.v. X is called Bernoulli if it takes only two values....
View Full Document

• Spring '00
• Akritas
• Probability theory, Binomial distribution, binomial random variable, Common Discrete Distributions, Michael Akritas

{[ snackBarMessage ]}

### Page1 / 64

b.lect10 - Outline Some Common Discrete Distributions...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online