1. (f) Use continuity corrections for discrete random variable LEARNING OUTCOMES At the end of the lesson, students will be able to (g) Use the normal.

Slides:



Advertisements
Similar presentations
Lecture 7. Distributions
Advertisements

Presentation on Probability Distribution * Binomial * Chi-square
Acknowledgement: Thanks to Professor Pagano
Week11 Parameter, Statistic and Random Samples A parameter is a number that describes the population. It is a fixed number, but in practice we do not know.
Poisson approximation to a Binomial distribution
Chapter 6 Some Special Discrete Distributions
Binomial Distributions
Normal Distribution * Numerous continuous variables have distribution closely resemble the normal distribution. * The normal distribution can be used to.
1. Variance of Probability Distribution 2. Spread 3. Standard Deviation 4. Unbiased Estimate 5. Sample Variance and Standard Deviation 6. Alternative Definitions.
Chapter 5 Basic Probability Distributions
LARGE SAMPLE TESTS ON PROPORTIONS
“Teach A Level Maths” Statistics 1
Chapter 5 Discrete Probability Distribution I. Basic Definitions II. Summary Measures for Discrete Random Variable Expected Value (Mean) Variance and Standard.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 4 and 5 Probability and Discrete Random Variables.
CA200 Quantitative Analysis for Business Decisions.
HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2010 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Chapter 8 Continuous.
Normal Approximation Of The Binomial Distribution:
Binomial Distributions Calculating the Probability of Success.
Business and Finance College Principles of Statistics Eng. Heba Hamad 2008.
Using Normal Distribution to Approximate a Discrete Distribution.
Poisson Random Variable Provides model for data that represent the number of occurrences of a specified event in a given unit of time X represents the.
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted by.
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted by.
MATB344 Applied Statistics Chapter 5 Several Useful Discrete Distributions.
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted by.
Bernoulli Trials Two Possible Outcomes –Success, with probability p –Failure, with probability q = 1  p Trials are independent.
CHAPTER Discrete Models  G eneral distributions  C lassical: Binomial, Poisson, etc Continuous Models  G eneral distributions 
Chapter 4. Discrete Random Variables A random variable is a way of recording a quantitative variable of a random experiment. A variable which can take.
King Saud University Women Students
Week11 Parameter, Statistic and Random Samples A parameter is a number that describes the population. It is a fixed number, but in practice we do not know.
Normal Approximations to Binomial Distributions. 
1 Since everything is a reflection of our minds, everything can be changed by our minds.
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted.
4.1 Probability Distributions Important Concepts –Random Variables –Probability Distribution –Mean (or Expected Value) of a Random Variable –Variance and.
Unit 11 Binomial Distribution IT Disicipline ITD1111 Discrete Mathematics & Statistics STDTLP 1 Unit 11 Binomial Distribution.
Normal approximation of Binomial probabilities. Recall binomial experiment:  Identical trials  Two outcomes: success and failure  Probability for success.
THE NORMAL APPROXIMATION TO THE BINOMIAL. Under certain conditions the Normal distribution can be used as an approximation to the Binomial, thus reducing.
Normal Distribution * Numerous continuous variables have distribution closely resemble the normal distribution. * The normal distribution can be used to.
Probability Distributions, Discrete Random Variables
 A probability function is a function which assigns probabilities to the values of a random variable.  Individual probability values may be denoted.
Normal Approximations to Binomial Distributions.  For a binomial distribution:  n = the number of independent trials  p = the probability of success.
Central Limit Theorem Let X 1, X 2, …, X n be n independent, identically distributed random variables with mean  and standard deviation . For large n:
Normal approximation to Binomial Only applicable for: Large n P not to small or large ie near 0.5 X~N(np, npq) Find the probability of obtaining 5 heads.
Chapter 6 Large Random Samples Weiqi Luo ( 骆伟祺 ) School of Data & Computer Science Sun Yat-Sen University :
Introduction A probability distribution is obtained when probability values are assigned to all possible numerical values of a random variable. It may.
PROBABILITY AND STATISTICS WEEK 5 Onur Doğan. The Binomial Probability Distribution There are many experiments that conform either exactly or approximately.
1. 2 At the end of the lesson, students will be able to (c)Understand the Binomial distribution B(n,p) (d) find the mean and variance of Binomial distribution.
12.1 Discrete Probability Distributions (Poisson Distribution)
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Copyright © Cengage Learning. All rights reserved. 8 PROBABILITY DISTRIBUTIONS AND STATISTICS.
THE NORMAL DISTRIBUTION
12.SPECIAL PROBABILITY DISTRIBUTIONS
Chapter 3 Probability Distribution.  A probability function is a function which assigns probabilities to the values of a random variable.  Individual.
Final Review.  On the Saturday after Christmas, it has been estimated that about 14.3% of all mall-goers are there to return or exchange holiday gifts.
Chapter 3 Probability Distribution Normal Distribution.
Probability Distributions  A variable (A, B, x, y, etc.) can take any of a specified set of values.  When the value of a variable is the outcome of a.
Chapter 3 Probability Distribution
Probability Distributions
CHAPTER 6 Random Variables
Blockbusters The aim for blue team is to get from one side to the other. The aim for white team is to get from the bottom to the top. Either team may answer.
Random Variables Review Game
The Normal Approximation to the Binomial Distribution
Econometric Models The most basic econometric model consists of a relationship between two variables which is disturbed by a random error. We need to use.
Normal Approximations to the Binomial Distribution
Probability distributions
Quantitative Methods Varsha Varde.
Continuous Random Variable Normal Distribution
Introduction to Probability and Statistics
S2.3 Continuous distributions
Presentation transcript:

1

(f) Use continuity corrections for discrete random variable LEARNING OUTCOMES At the end of the lesson, students will be able to (g) Use the normal distribution to approximate binomial distribution 2

The Approximation from Binomial Distribution to Normal Distribution to Normal Distribution Under certain circumstances, normal distribution can be used as an approximation to Binomial Distribution with Where This approximation is used when (i) The value of n is large (ii) The value of p is close to 0.5 3

CONTINUITY CORRECTION Suppose a coin tossed 12 times. If we required the probability that there are not more than three head, i.e then we consider So P( X  3) transforms to P( X < 3.5 ), i.e. P( X  3)  P( X < 3.5 )

CONTINUITY CORRECTION 5

CONTINUITY CORRECTION 6

Example The area of rectangle should be considered

The area of rectangle should not be considered

Only the area of rectangle should be considered

Example 1 Write down each probability below after continuity correction 12

13

Example 2 Let, use the binomial approximation to find 14

Solution Given, where n = 200, p = 0.3, q=0.7. Normal approximation 15

16

17

18

19

20

Example 3 Find the probability of obtaining between 4 and 6 heads ( inclusive) when tossing a fair coin 12 times, by using a) The binomial distribution b) The normal approximation to the binomial distribution 21

Solution Let X = the number of heads obtained Then, 22

b) Using the normal approximation 23

Example 4 A fair coin is tossed 400 times. Find the probability of getting a) Less than 230 tails b) Exactly 205 tails c) Between 180 and 190 tails solution Let X = the number of tails obtained Then, The normal approximation 24

25

26

27

The Approximation from Poisson Distribution to Normal Distribution Under certain circumstances, normal distribution can be used as an approximation to Poisson Distribution with This approximation is used when the value of 28

Example 6 29

Solution 30

Example 7 The number of complain received by a telecommunication company has a Poisson distribution with mean 10 complain per day. Find the probability that: (a) there were more than 10 complain received in a day (b) at least 50 complain in a week 31

Solution 32

33

Example 8 Assume that the number of s received by a student daily has a Poison Distribution with a mean of 5. a) Determine the probability that the student receives between 5 and 13 s daily. b) If 15 days are randomly chosen, find the probability that the student receives between 5 and 13 s daily for a period of 9 days. 34

c) If 150 days are randomly chosen, use the normal approximation to find the probability that the student receives between 5 and 13 s daily for less than 70 days. 35

Solution Let X= number of s received by a student daily. 36

37

38 Let Y= number of students receive between 5 and 13 s daily

39

Example 9 The number of asbestos particles in a squared centimeter of dust is found to follow a Poisson distribution with a mean of If a random squared centimeter of dust is analysed, what is the probability that less than 950 particles are found? 40

Solution Using the normal approximation : 41

Example 10 Ten present of tiles produced in a factory are broken before they are packed. If a random sample of 500 tiles is taken, find the probability of getting a) Less than 40 broken tiles b) At least 40 broken tiles c) Between 50 and 56 broken tiles ( inclusive) d) At most 30 broken tiles 42

solution Let X = the number of broken tiles obtained.Then, The normal approximation 43

44

45

46

47

Using the Poisson Distribution as an Approximation to the Binomial distribution It is appropriate to use the Poisson distribution as an approximation to the binomial when (i) n is large ( n > 50 ) or / and (ii) p is small ( p < 0. 1 ) In fact, when p = 0.1, n 30, both Poisson and binomial distribution are almost identical. This particular approximation is more accurate when p 0 and n ( for Poisson ) = np ( for binomial) 48

The Approximation from Binomial Distribution to Normal Distribution to Normal Distribution Normal distribution can be used as an approximation to Binomial Distribution with Where q = 1-p This approximation is used when (i) The value of n is large (ii) The value of p is close to

The Approximation from Poisson Distribution to Normal Distribution to Normal Distribution Under certain circumstances, normal distribution can be used as an approximation to Poisson Distribution with This approximation is used when the value of 50

Exercise The discrete random variable X is found to follow a Poisson distribution with a mean of 200. Use the Normal approximation of this Poisson distribution to find : Answer : (a) 0.65 (b)