Slide Slide 1 Section 6-6 Normal as Approximation to Binomial.

Slides:



Advertisements
Similar presentations
Normal Approximations to Binomial Distributions Larson/Farber 4th ed1.
Advertisements

Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Lecture Slides Elementary Statistics Twelfth Edition
Section 7.4 Approximating the Binomial Distribution Using the Normal Distribution HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008.
Slide 1 Copyright © 2004 Pearson Education, Inc.  Continuous random variable  Normal distribution Overview Figure 5-1 Formula 5-1 LAPTOP3: f(x) = 
Applications of Normal Distributions
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Section 6-6 Normal as Approximation to Binomial Created by.
Chapter 4 Probability Distributions
Definitions Uniform Distribution is a probability distribution in which the continuous random variable values are spread evenly over the range of possibilities;
Chapter 6 Normal Probability Distributions
7-2 Estimating a Population Proportion
Lecture Slides Elementary Statistics Twelfth Edition
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Slide 1 Statistics Workshop Tutorial 7 Discrete Random Variables Binomial Distributions.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Slide 1 Copyright © 2004 Pearson Education, Inc..
Density Curve A density curve is the graph of a continuous probability distribution. It must satisfy the following properties: 1. The total area.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
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:
Section 5.5 Normal Approximations to Binomial Distributions Larson/Farber 4th ed.
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Normal Distribution as an Approximation to the Binomial Distribution Section 5-6.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Review and Preview This chapter combines the methods of descriptive statistics presented in.
Slide 1 Copyright © 2004 Pearson Education, Inc..
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Chapter 7 Estimates and Sample Sizes
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Lecture Slides Elementary Statistics Tenth Edition and the.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6. Continuous Random Variables Reminder: Continuous random variable.
Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution 6-3 Applications of Normal Distributions 6-4 Sampling Distributions.
Statistics Workshop Tutorial 8 Normal Distributions.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 6 Normal Probability Distributions 6-1 Review and Preview 6-2 The Standard Normal.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved Section 8-3 Testing a Claim About a Proportion.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Statistics Section 5-6 Normal as Approximation to Binomial.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 6 Normal Probability Distributions 6-1 Review and Preview 6-2 The Standard Normal.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 7-1 Review and Preview.
Slide Slide 1 Lecture 6&7 CHS 221 Biostatistics Dr. Wajed Hatamleh.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Chapter 6 Normal Probability Distributions 6-1 Overview 6-2.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6 Continuous Random Variables.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 6-3 Applications of Normal Distributions.
Normal Approximations to Binomial Distributions.  For a binomial distribution:  n = the number of independent trials  p = the probability of success.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Slide Slide 1 Suppose we are interested in the probability that z is less than P(z < 1.42) = z*z*
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Normal Probability Distributions 5.
Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance and Standard Deviation.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Slide 1 Copyright © 2004 Pearson Education, Inc. Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution 6-3 Applications.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Created by Tom Wegleitner, Centreville, Virginia Section 5-3.
Slide 1 Copyright © 2004 Pearson Education, Inc. Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability Distributions.
Chapter 6 Normal Approximation to Binomial Lecture 4 Section: 6.6.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Section 6-2 The Standard Normal Distribution.
Chapter 5 Normal Probability Distributions.
Lecture Slides Elementary Statistics Twelfth Edition
Chapter 6. Continuous Random Variables
The Standard Normal Distribution
Normal as Approximation to Binomial
Lecture Slides Elementary Statistics Eleventh Edition
Lecture Slides Elementary Statistics Tenth Edition
Elementary Statistics
Elementary Statistics
Lecture Slides Elementary Statistics Twelfth Edition
Normal Probability Distributions
The Standard Normal Distribution
Section 6-1 Review and Preview.
Chapter 5 Section 5-5.
Section 6-1 Review and Preview.
Lecture Slides Elementary Statistics Twelfth Edition
Chapter 5 Normal Probability Distributions.
Normal as Approximation to Binomial
Lecture Slides Essentials of Statistics 5th Edition
Presentation transcript:

Slide Slide 1 Section 6-6 Normal as Approximation to Binomial

Slide Slide 2 Key Concept This section presents a method for using a normal distribution as an approximation to the binomial probability distribution. If the conditions of np ≥ 5 and nq ≥ 5 are both satisfied, then probabilities from a binomial probability distribution can be approximated well by using a normal distribution with mean μ = np and standard deviation σ = √npq

Slide Slide 3 Review Binomial Probability Distribution: 2NIP 1. The procedure must have fixed number of trials. 2. The trials must be independent. 3. Each trial must have all outcomes classified into two categories. 4.The probability of success remains the same in all trials. Solve by binomial probability formula, Table A-1, or technology.

Slide Slide 4 Approximation of a Binomial Distribution with a Normal Distribution np  5 nq  5 then µ = np and  = npq and the random variable has distribution. (normal) a

Slide Slide 5 Procedure for Using a Normal Distribution to Approximate a Binomial Distribution 1. Establish that the normal distribution is a suitable approximation to the binomial distribution by verifying np  5 and nq  Find the values of the parameters µ and  by calculating µ = np and  = npq. 3.Identify the discrete value of x (the number of successes). Change the discrete value x by replacing it with the interval from x – 0.5 to x (See continuity corrections discussion later in this section.) Draw a normal curve and enter the values of µ, , and either x – 0.5 or x + 0.5, as appropriate. 4. Change x by replacing it with x – 0.5 or x + 0.5, as appropriate. 5. Using x – 0.5 or x (as appropriate) in place of x, find the area corresponding to the desired probability by first finding the z score and finding the area to the left of the adjusted value of x.

Slide Slide 6 Example – p. 293: Number of Men Among Passengers An American Airlines Boeing aircraft has 213 seats. When fully loaded with passengers, baggage, cargo, and fuel, the pilot must verify that the gross weight is below the maximum allowable limit, and the weight must be properly distributed so that the balance of the aircraft is within safe acceptable limits. Instead of weighing each passenger, their weights are estimated according to Federal Aviation Administration rules. In reality, we know that men have a mean weight of 172 pounds, whereas women have a mean weight of 143 pounds, so disproportionately more male passengers might result in an unsafe overweight situation. Assume that if there are at least 122 men in a roster of 213 passengers, the load must be somehow adjusted. Assuming that passengers are booked randomly, male passengers and female passengers are equally likely, and the aircraft is full of adults, find the probability that a Boeing with 213 passengers has at least 122 men.

Slide Slide 7 Figure 6-21 Finding the Probability of “At Least 122 Men” Among 213 Passengers

Slide Slide 8 Procedure for Continuity Corrections 1. When using the normal distribution as an approximation to the binomial distribution, always use the continuity correction. 2. In using the continuity correction, first identify the discrete whole number x that is relevant to the binomial probability problem. 3. Draw a normal distribution centered about µ, then draw a vertical strip area centered over x. Mark the left side of the strip with the number x – 0.5, and mark the right side with x For x = 122, draw a strip from to Consider the area of the strip to represent the probability of discrete whole number x.

Slide Slide 9 4. Now determine whether the value of x itself should be included in the probability you want. Next, determine whether you want the probability of at least x, at most x, more than x, fewer than x, or exactly x. Shade the area to the right or left of the strip, as appropriate; also shade the interior of the strip itself if and only if x itself is to be included. The total shaded region corresponds to the probability being sought. Procedure for Continuity Corrections - cont

Slide Slide 10 x = at least 122 (includes 122 and above) x = more than 122 (doesn’t include 122) x = at most 122 (includes 122 and below) x = fewer than 122 (doesn’t include 122) x = exactly 122 Figure 6-22

Slide Slide 11 Definition When we use the normal distribution (which is a continuous probability distribution) as an approximation to the binomial distribution (which is discrete), a continuity correction is made to a discrete whole number x in the binomial distribution by representing the single value x by the interval from x – 0.5 to x (that is, adding and subtracting 0.5).

Slide Slide 12 Example: Internet use A recent survey showed that among 213 randomly selected adults, 1358 (or 65.7%) stated that they are Internet users (based on data from Pew Research Center). If the proportion of all adults using the Internet is actually 2/3, find the probability that a random sample of 2013 adults will result in exactly 1358 Internet users.

Slide Slide 13 Recap In this section we have discussed:  Approximating a binomial distribution with a normal distribution.  Procedures for using a normal distribution to approximate a binomial distribution.  Continuity corrections.