Ch3.5 Hypergeometric Distribution

Slides:



Advertisements
Similar presentations
Discrete Random Variables and Probability Distributions
Advertisements

Discrete Uniform Distribution
DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS
The Bernoulli distribution Discrete distributions.
Dr. Engr. Sami ur Rahman Data Analysis Lecture 4: Binomial Distribution.
Probability Distribution
Class notes for ISE 201 San Jose State University
Discrete Probability Distributions Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Review.
Hypergeometric Random Variables. Sampling without replacement When sampling with replacement, each trial remains independent. For example,… If balls are.
Probability Distributions
A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.
Discrete Random Variables and Probability Distributions
C4: DISCRETE RANDOM VARIABLES CIS 2033 based on Dekking et al. A Modern Introduction to Probability and Statistics Longin Jan Latecki.
Class notes for ISE 201 San Jose State University
Chapter 21 Random Variables Discrete: Bernoulli, Binomial, Geometric, Poisson Continuous: Uniform, Exponential, Gamma, Normal Expectation & Variance, Joint.
Copyright © Cengage Learning. All rights reserved. 3.5 Hypergeometric and Negative Binomial Distributions.
Copyright © Cengage Learning. All rights reserved. 3.4 The Binomial Probability Distribution.
Discrete Probability Distributions
Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.
Probability Distribution
Binomial distribution Nutan S. Mishra Department of Mathematics and Statistics University of South Alabama.
HW adjustment Q70 solve only parts a, b, and d. Q76 is moved to the next homework and added-Q2 is moved to the next homework as well.
The Negative Binomial Distribution An experiment is called a negative binomial experiment if it satisfies the following conditions: 1.The experiment of.
Random Variables Section 3.1 A Random Variable: is a function on the outcomes of an experiment; i.e. a function on outcomes in S. For discrete random variables,
4.5 Comparing Discrete Probability Distributions.
Math 22 Introductory Statistics Chapter 8 - The Binomial Probability Distribution.
COMP 170 L2 L17: Random Variables and Expectation Page 1.
Methodology Solving problems with known distributions 1.
The Binomial Distribution
4.2 Binomial Distributions
Ch. 15H continued. * -applied to experiments with replacement ONLY(therefore…..independent events only) * -Note: For DEPENDENT events we use the “hypergeometric.
Exam 2: Rules Section 2.1 Bring a cheat sheet. One page 2 sides. Bring a calculator. Bring your book to use the tables in the back.
4.3 More Discrete Probability Distributions NOTES Coach Bridges.
Discrete Probability Distributions Chapter 4. § 4.2 Binomial Distributions.
Chapter 7 Section 5.  Binomial Distribution required just two outcomes (success or failure).  Multinomial Distribution can be used when there are more.
Chapter 3 Discrete Random Variables and Probability Distributions  Random Variables.2 - Probability Distributions for Discrete Random Variables.3.
Copyright © Cengage Learning. All rights reserved. 3 Discrete Random Variables and Probability Distributions.
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 5 Discrete Random Variables.
PROBABILITY AND STATISTICS WEEK 5 Onur Doğan. The Binomial Probability Distribution There are many experiments that conform either exactly or approximately.
MATH 2311 Section 3.3.
Chap 5-1 Chapter 5 Discrete Random Variables and Probability Distributions Statistics for Business and Economics 6 th Edition.
Copyright © Cengage Learning. All rights reserved. 3 Discrete Random Variables and Probability Distributions.
3.1 Discrete Random Variables Present the analysis of several random experiments Discuss several discrete random variables that frequently arise in applications.
8.2 The Geometric Distribution 1.What is the geometric setting? 2.How do you calculate the probability of getting the first success on the n th trial?
The binomial probability distribution
Chapter 3 Discrete Random Variables and Probability Distributions
MATH 2311 Section 3.3.
Negative Binomial Experiment
The hypergeometric and negative binomial distributions
Discrete Random Variables and Probability Distributions
Math 4030 – 4a More Discrete Distributions
Discrete Random Variables
Random Variables.
Probability Distributions
Hypergeometric Distribution
Probability Distributions
Chapter 3 Discrete Random Variables and Probability Distributions
PROBABILITY AND STATISTICS
Chapter 5: Some Discrete Probability Distributions:
Chapter 3 Discrete Random Variables and Probability Distributions
Some Discrete Probability Distributions
ASV Chapters 1 - Sample Spaces and Probabilities
Section 3: Estimating p in a binomial distribution
Discrete Variables Classes
If the question asks: “Find the probability if...”
Bernoulli Trials Two Possible Outcomes Trials are independent.
Each Distribution for Random Variables Has:
MATH 2311 Section 3.3.
Presentation transcript:

Ch3.5 Hypergeometric Distribution If X is the number of S’s in a completely random sample of size n drawn from a population consisting of M S’s and (N – M) F’s, then the probability distribution of X, called the hypergeometric distribution, is given by Mean and Variance Ch3.5

Ch3.5 The negative binomial RV and distribution are based on an experiment satisfying the following four conditions: The experiment consists of a sequence of independent trials. Each trial can result in a success (S) or a failure (F). The probability of success is constant from trial to trial, so P(S on trial i) = p for i = 1, 2, 3, … The experiment continues until a total of r successes have been observed, where r is a specified positive integer. Ch3.5

Ch3.5 The pmf of the negative binomial RV X with parameters r = number of S’s and p = P(S) is x = 0, 1, 2, … Mean and Variance Ch3.5