PROBABILITY AND STATISTICS WEEK 5 Onur Doğan. The Binomial Probability Distribution There are many experiments that conform either exactly or approximately.

Slides:



Advertisements
Similar presentations
Discrete Random Variables and Probability Distributions
Advertisements

MOMENT GENERATING FUNCTION AND STATISTICAL DISTRIBUTIONS
Discrete Uniform Distribution
DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS
Introduction to Probability and Statistics Chapter 5 Discrete Distributions.
Chapter 5 Discrete Random Variables and Probability Distributions
The Bernoulli distribution Discrete distributions.
ฟังก์ชั่นการแจกแจงความน่าจะเป็น แบบไม่ต่อเนื่อง Discrete Probability Distributions.
Statistics for Managers Using Microsoft Excel, 5e © 2008 Pearson Prentice-Hall, Inc.Chap 5-1 Statistics for Managers Using Microsoft® Excel 5th Edition.
Chapter 4 Discrete Random Variables and Probability Distributions
Discrete Random Variables and Probability Distributions
1 1 Slide 2009 University of Minnesota-Duluth, Econ-2030 (Dr. Tadesse) Chapter 5: Probability Distributions: Discrete Probability Distributions.
Review.
Hypergeometric Random Variables. Sampling without replacement When sampling with replacement, each trial remains independent. For example,… If balls are.
Probability Distributions
Chapter 5 Probability Distributions
Discrete Random Variables and Probability Distributions
Chapter 5 Discrete Random Variables and Probability Distributions
Binomial Distributions
Discrete Probability Distributions Binomial Distribution Poisson Distribution Hypergeometric Distribution.
Chapter 5 Several Discrete Distributions General Objectives: Discrete random variables are used in many practical applications. These random variables.
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.
Lesson 6 – 2b Hyper-Geometric Probability Distribution.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 4 and 5 Probability and Discrete Random Variables.
6- 1 Chapter Six McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
Probability Distribution
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. A random variable X is a real valued function defined on the sample space, X : S  R. The set { s  S : X ( s )  [ a, b ] is an event}.
HYPERGEOMETRIC DISTRIBUTION PREPARED BY :A.TUĞBA GÖRE
Binomial Experiment A binomial experiment (also known as a Bernoulli trial) is a statistical experiment that has the following properties:
Math 4030 – 4a Discrete Distributions
1 1 Slide University of Minnesota-Duluth, Econ-2030 (Dr. Tadesse) University of Minnesota-Duluth, Econ-2030 (Dr. Tadesse) Chapter 5: Probability Distributions:
Copyright © 2006 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide
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.
Discrete Random Variables. Discrete random variables For a discrete random variable X the probability distribution is described by the probability function,
Chapter 4-5 DeGroot & Schervish. Conditional Expectation/Mean Let X and Y be random variables such that the mean of Y exists and is finite. The conditional.
PROBABILITY AND STATISTICS WEEK 4 Onur Doğan. Random Variable Random Variable. Let S be the sample space for an experiment. A real-valued function that.
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted.
DISCRETE PROBABILITY MODELS
Chapter 4. Random Variables - 3
Copyright © Cengage Learning. All rights reserved. 3 Discrete Random Variables and Probability Distributions.
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.
Chapter 5 Special Distributions Weiqi Luo ( 骆伟祺 ) School of Data & Computer Science Sun Yat-Sen University :
Onur DOĞAN. ..  ljhlj  Suppose that a machine produces defective item with probability 0,1. a) When we select 5 items, find the probability of 1.
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc. Chap 5-1 Chapter 5 Some Important Discrete Probability Distributions Business Statistics,
Random Probability Distributions BinomialMultinomial Hyper- geometric
Chap 5-1 Discrete and Continuous Probability Distributions.
Chapter 4 Discrete Random Variables and Probability Distributions
Copyright © Cengage Learning. All rights reserved. 3 Discrete Random Variables and Probability Distributions.
The binomial probability distribution
Ch3.5 Hypergeometric Distribution
The hypergeometric and negative binomial distributions
Discrete Random Variables and Probability Distributions
3 Discrete Random Variables and Probability Distributions
Random variables (r.v.) Random variable
Random Variables.
Samples and Populations
ENGR 201: Statistics for Engineers
Discrete Random Variables and Probability Distributions
PROBABILITY AND STATISTICS
Introduction to Probability and Statistics
Distributions and expected value
Probability Theory and Specific Distributions (Moore Ch5 and Guan Ch6)
Discrete Random Variables and Probability Distributions
Each Distribution for Random Variables Has:
Geometric Poisson Negative Binomial Gamma
PROBABILITY AND STATISTICS
Presentation transcript:

PROBABILITY AND STATISTICS WEEK 5 Onur Doğan

The Binomial Probability Distribution There are many experiments that conform either exactly or approximately to the following list of requirements: 1. The experiment consists of a sequence of n smaller experiments called trials, where n is fixed in advance of the experiment. 2. Each trial can result in one of the same two possible outcomes (dichotomous trials), which we denote by success (S) and failure (F). 3. The trials are independent, so that the outcome on any particular trial does not influence the outcome on any other trial. 4. The probability of success is constant from trial to trial; we denote this probability by p. An experiment for which Conditions 1–4 are satisfied is called a binomial experiment. Onur Doğan

Bernoulli trials A Bernoulli refers to a trial that has only two possible outcomes. (1) Flipping a coin: S = {head, tail) (2) Truth of an answer: S = {right, wrong) (3) Status of a machine: S = {working, broken) (4) Quality of a product: S = {good, defective) (5) Accomplishment of a task: S = {success, failure) A binomial experiment consists of a series of n independent Bernoulli trials with a constant probability of success (p) in each trial. Onur Doğan

Example A seller’s success ? Onur Doğan

The Mean and Variance of X Onur Doğan

Example Suppose that a machine produce defective item with probability 0,1. a) Suppose that we selected 5 items, find the probability of 1 item defective. b) If the amount of daily production is 100, then what's the expected defective item amount? c)What’s the variance of defective items of samples around the expected defective items. Onur Doğan

Example The probability of making a doctor's successful surgery is %80. If that doctor make 3 surgery in one month, find the all probability for all possible results. Onur Doğan

Example In a certain automobile dealership, 20% of all customers purchase an extended warranty with their new car. For 7 customers selected at random: 1)Find the probability that exactly 2 will purchase an extended warranty 2)Find the probability at most 6 will purchase an extended warranty Onur Doğan

Solutions: 1)n = 18, p = 0.75, q = = 0.25  np()(0.)  npq()(0. ) Example Example:Find the mean and standard deviation of the binomial distribution when n = 18 and p = Define the probability function. Px x x xx ()(0.) )          for0, 1, 2,..., 18 2)The probability function is:

The Hypergeometric Distribution The assumptions leading to the hypergeometric distribution are as follows: 1.The population or set to be sampled consists of N individuals, objects, or elements (a finite population). 2. Each individual can be characterized as a success (S) or a failure (F), and there are M successes in the population. 3. A sample of n individuals is selected without replacement in such a way that each subset of size n is equally likely to be chosen. The random variable of interest is X the number of S’s in the sample. The probability distribution of X depends on the parameters n, M, and N, so we wish to obtain P(X x) h(x; n, M, N). Onur Doğan

Example Suppose that a box contains five red balls and ten blue balls. If seven balls are selected at random without replacement, what is the probability that three red balls will be obtained? Onur Doğan

The Hypergeometric Distribution Onur Doğan

Example Suppose that in production line for every 20 products, 4 of them enter reprocessing. a) If we selected 2 products, find the probability of one of them enter reprocessing? b) If we selected 10 products, how many of them should have expected enter reprocessing? Onur Doğan

Note: The hypergeometric distribution is related to the binomial distribution. Whereas the binomial distribution is the approximate probability model for sampling without replacement from a finite dichotomous (S–F) population, the hypergeometric distribution is the exact probability model for the number of S’s in the sample. Onur Doğan

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

The Negative Binomial Distribution Onur Doğan

Example A pediatrician wishes to recruit 5 couples, each of whom is expecting their first child, to participate in a new natural childbirth regimen. Let p=P(a randomly selected couple agrees to participate). If p=0.2, what is the probability that 15 couples must be asked before 5 are found who agree to participate? Onur Doğan

The Negative Binomial Distribution Onur Doğan

The Geometric Distributions Onur Doğan

Example In a production line 200 of 1000 items were found to be defective. a)What’s the probability of first defective item is the 4th item tested. b)How many items should have been tested till first defective item found? c)What’s the probability of the first defective item is not the first tested one? Onur Doğan

The Multinomial Distributions Onur Doğan

Example Suppose that there are 3 different brand; A,B and C. And we have probabilities to be purchased; P(A)=0,40 P(B)=0,10 P(C)=0,50 Suppose that there are 10 customers, what’s the probability of 2 of them buy A, 5 of them buy B and 3 of them buy C. Onur Doğan

The Poisson Probability Distribution Onur Doğan

Example Suppose that, in İzmir the number of power blackout has the Poisson distribution with mean 2, for one year. Find the probability of there will be no power blackout in next year? Find the probability of there will be 2 power blackout in next 6 months? Find the probability of there will be 2 or more blackout in next year? Onur Doğan

Example The number of requests for assistance received by a towing service is a Poisson process with rate  =4 per hour. a. Compute the probability that exactly ten requests are received during a particular 2-hour period. b. If the operators of the towing service take a 30-min break for lunch, what is the probability that they do not miss any calls for assistance? c. How many calls would you expect during their break? Onur Doğan