Chapter. Section 4.2. Chapter 4. Larson/Farber 5 th ed 1. Chapter Outline. Discrete Probability Distributions. Section 4.

Size: px
Start display at page:

Download "Chapter. Section 4.2. Chapter 4. Larson/Farber 5 th ed 1. Chapter Outline. Discrete Probability Distributions. Section 4."

Transcription

1 Chapter Discrete Probability s Chapter Outline 1 Probability s 2 Binomial s 3 More Discrete Probability s Copyright 2015, 2012, and 2009 Pearson Education, Inc 1 Copyright 2015, 2012, and 2009 Pearson Education, Inc 2 Section 2 Objectives Section 2 Binomial s How to determine whether a probability experiment is a binomial experiment How to find binomial probabilities using the binomial probability formula How to find binomial probabilities using technology, formulas, and a binomial table How to construct and graph a binomial distribution How to find the mean, variance, and standard deviation of a binomial probability distribution Copyright 2015, 2012, and 2009 Pearson Education, Inc 3 Copyright 2015, 2012, and 2009 Pearson Education, Inc Binomial Experiments Notation for Binomial Experiments 1 The experiment is repeated for a fixed number of trials, where each trial is independent of other trials 2 There are only two possible outcomes of interest for each trial The outcomes can be classified as a success (S) or as a failure (F) 3 The probability of a success, P(S), is the same for each trial The random variable x counts the number of successful trials Symbol n p = P(S) q = P(F) x Description The number of times a trial is repeated The probability of success in a single trial The probability of failure in a single trial (q = 1 p) The random variable represents a count of the number of successes in n trials: x = 0, 1, 2, 3,, n Copyright 2015, 2012, and 2009 Pearson Education, Inc 5 Copyright 2015, 2012, and 2009 Pearson Education, Inc 6 Larson/Farber 5 th ed 1

2 Example: Binomial Experiments Decide whether the experiment is a binomial experiment If it is, specify the values of n, p, and q, and list the possible values of the random variable x 1 A certain surgical procedure has an 85% chance of success A doctor performs the procedure on eight patients The random variable represents the number of successful surgeries Binomial Experiments Binomial Experiment 1 Each surgery represents a trial There are eight surgeries, and each one is independent of the others 2 There are only two possible outcomes of interest for each surgery: a success (S) or a failure (F) 3 The probability of a success, P(S), is 085 for each surgery The random variable x counts the number of successful surgeries Copyright 2015, 2012, and 2009 Pearson Education, Inc 7 Copyright 2015, 2012, and 2009 Pearson Education, Inc 8 Binomial Experiments Binomial Experiment n = 8 (number of trials) p = 085 (probability of success) q = 1 p = = 015 (probability of failure) x = 0, 1, 2, 3,, 5, 6, 7, 8 (number of successful surgeries) Example: Binomial Experiments Decide whether the experiment is a binomial experiment If it is, specify the values of n, p, and q, and list the possible values of the random variable x 2 A jar contains five red marbles, nine blue marbles, and six green marbles You randomly select three marbles from the jar, without replacement The random variable represents the number of red marbles Copyright 2015, 2012, and 2009 Pearson Education, Inc 9 Copyright 2015, 2012, and 2009 Pearson Education, Inc 10 Binomial Experiments Not a Binomial Experiment The probability of selecting a red marble on the first trial is 5/20 Because the marble is not replaced, the probability of success (red) for subsequent trials is no longer 5/20 The trials are not independent and the probability of a success is not the same for each trial Binomial Probability Formula Binomial Probability Formula The probability of exactly x successes in n trials is n! P( x) = ncx p q = p q ( n x)! x! n = number of trials p = probability of success q = 1 p probability of failure x = number of successes in n trials Note: number of failures is n x x n x x n x Copyright 2015, 2012, and 2009 Pearson Education, Inc 11 Copyright 2015, 2012, and 2009 Pearson Education, Inc 12 Larson/Farber 5 th ed 2

3 Microfracture knee surgery has a 75% chance of success on patients with degenerative knees The surgery is performed on three patients Find the probability of the surgery being successful on exactly two patients Method 1: Draw a tree diagram and use the Multiplication Rule 9 P(2 successful surgeries) = Copyright 2015, 2012, and 2009 Pearson Education, Inc 13 Copyright 2015, 2012, and 2009 Pearson Education, Inc 1 Method 2: Binomial Probability Formula 3 1 n = 3, p =, q = 1 p =, x = = 3 2 P(2 successful surgeries) C 2 1 3! 3 1 = (3 2)!2! = 3 = Binomial Probability Binomial Probability List the possible values of x with the corresponding probability of each Example: Binomial probability distribution for Microfacture knee surgery: n = 3, p = x P(x) Use binomial probability formula to find probabilities 3 Copyright 2015, 2012, and 2009 Pearson Education, Inc 15 Copyright 2015, 2012, and 2009 Pearson Education, Inc 16 Example: Constructing a Binomial In a survey, US adults were asked to give reasons why they liked texting on their cellular phones Seven adults who participated in the survey are randomly selected and asked whether they like texting because it is quicker than Calling Create a binomial probability distribution for the number of adults who respond yes Constructing a Binomial 56% of adults like texting because it is quicker than calling n = 7, p = 056, q = 0, x = 0, 1, 2, 3,, 5, 6, 7 P(x = 0) = 7 C 0 (056) 0 (0) 7 = 1(056) 0 (0) P(x = 1) = 7 C 1 (056) 1 (0) 6 = 7(056) 1 (0) P(x = 2) = 7 C 2 (056) 2 (0) 5 = 21(056) 2 (0) P(x = 3) = 7 C 3 (056) 3 (0) = 35(056) 3 (0) 0230 P(x = ) = 7 C (056) (0) 3 = 35(056) (0) P(x = 5) = 7 C 5 (056) 5 (0) 2 = 21(056) 5 (0) P(x = 6) = 7 C 6 (056) 6 (0) 1 = 7(056) 6 (0) P(x = 7) = 7 C 7 (056) 7 (0) 0 = 1(056) 7 (0) Copyright 2015, 2012, and 2009 Pearson Education, Inc 17 Copyright 2015, 2012, and 2009 Pearson Education, Inc 18 Larson/Farber 5 th ed 3

4 Constructing a Binomial x P(x) All of the probabilities are between 0 and 1 and the sum of the probabilities is The results of a recent survey indicate that 67% of US adults consider air conditioning a necessity If you randomly select 100 adults, what is the probability that exactly 75 adults consider air conditioning a necessity? Use a technology tool to find the probability (Source: Opinion Research Corporation) Binomial with n = 100, p = 057, x = 75 Copyright 2015, 2012, and 2009 Pearson Education, Inc 19 Copyright 2015, 2012, and 2009 Pearson Education, Inc 20 Using Formulas A survey indicates that 1% of women in the US consider reading their favorite leisure-time activity You randomly select four US women and ask them if reading is their favorite leisure-time activity Find the probability that at least two of them respond yes From the displays, you can see that the probability that exactly 75 adults consider air conditioning a necessity is about 002 n =, p = 01, q = 059 At least two means two or more Find the sum of P(2), P(3), and P() Copyright 2015, 2012, and 2009 Pearson Education, Inc 21 Copyright 2015, 2012, and 2009 Pearson Education, Inc 22 Using Formulas P(x = 2) = C 2 (01) 2 (059) 2 = 6(01) 2 (059) P(x = 3) = C 3 (01) 3 (059) 1 = (01) 3 (059) P(x = ) = C (01) (059) 0 = 1(01) (059) P(x 2) = P(2) + P(3) + P() The results of a recent survey indicate that 67% of US adults consider air conditioning a necessity If you randomly select 100 adults, what is the probability that exactly 75 adults consider air conditioning a necessity? Use a technology tool to find the probability (Source: Opinion Research Corporation) Binomial with n = 100, p = 057, x = 75 Copyright 2015, 2012, and 2009 Pearson Education, Inc 23 Copyright 2015, 2012, and 2009 Pearson Education, Inc 2 Larson/Farber 5 th ed

5 Using a Table About ten percent of workers (16 years and over) in the United States commute to their jobs by carpooling You randomly select eight workers What is the probability that exactly four of them carpool to work? Use a table to find the probability (Source: American Community Survey) From the displays, you can see that the probability that exactly 75 adults consider air conditioning a necessity is about 002 Binomial with n = 8, p = 010, x = Copyright 2015, 2012, and 2009 Pearson Education, Inc 25 Copyright 2015, 2012, and 2009 Pearson Education, Inc 26 Using a Table A portion of Table 2 is shown The probability that exactly four of the eight workers carpool to work is 0005 Example: Graphing a Binomial Sixty percent of households in the US own a video game console You randomly select six households and ask each if they own a video game console Construct a probability distribution for the random variable x Then graph the distribution (Source: Deloitte, LLP) n = 6, p = 06, q = 0 Find the probability for each value of x Copyright 2015, 2012, and 2009 Pearson Education, Inc 27 Copyright 2015, 2012, and 2009 Pearson Education, Inc 28 Graphing a Binomial x P(x) Histogram: Mean, Variance, and Standard Deviation Mean: μ = np Variance: σ 2 = npq Standard Deviation: σ = npq Copyright 2015, 2012, and 2009 Pearson Education, Inc 29 Copyright 2015, 2012, and 2009 Pearson Education, Inc 30 Larson/Farber 5 th ed 5

6 Example: Finding the Mean, Variance, and Standard Deviation In Pittsburgh, Pennsylvania, about 56% of the days in a year are cloudy Find the mean, variance, and standard deviation for the number of cloudy days during the month of June Interpret the results and determine any unusual values (Source: National Climatic Data Center) n = 30, p = 056, q = 0 Mean: μ = np = = 168 Variance: σ 2 = npq = Standard Deviation: σ = npq = Finding the Mean, Variance, and Standard Deviation μ = 168 σ 2 7 σ 27 On average, there are 168 cloudy days during the month of June The standard deviation is about 27 days Values that are more than two standard deviations from the mean are considered unusual 168 2(27) =11; A June with 11 cloudy days or less would be unusual (27) = 222; A June with 23 cloudy days or more would also be unusual Copyright 2015, 2012, and 2009 Pearson Education, Inc 31 Copyright 2015, 2012, and 2009 Pearson Education, Inc 32 Section 2 Summary Determined if a probability experiment is a binomial experiment Found binomial probabilities using the binomial probability formula Found binomial probabilities using technology, formulas, and a binomial table Constructed and graphed a binomial distribution Found the mean, variance, and standard deviation of a binomial probability distribution Copyright 2015, 2012, and 2009 Pearson Education, Inc 33 Larson/Farber 5 th ed 6

Stats SB Notes 4.2 Completed.notebook February 22, Feb 21 11:39 AM. Chapter Outline

Stats SB Notes 4.2 Completed.notebook February 22, Feb 21 11:39 AM. Chapter Outline Stats SB Notes 42 Completednotebook February 22, 2017 Chapter 4 Discrete Probability Distributions Chapter Outline 41 Probability Distributions 42 Binomial Distributions 43 More Discrete Probability Distributions

More information

Chapter 4. Section 4.1 Objectives. Random Variables. Random Variables. Chapter 4: Probability Distributions

Chapter 4. Section 4.1 Objectives. Random Variables. Random Variables. Chapter 4: Probability Distributions Chapter 4: Probability s 4. Probability s 4. Binomial s Section 4. Objectives Distinguish between discrete random variables and continuous random variables Construct a discrete probability distribution

More information

Binomial Distributions

Binomial Distributions Binomial Distributions Binomial Experiment The experiment is repeated for a fixed number of trials, where each trial is independent of the other trials There are only two possible outcomes of interest

More information

Binomial Distributions

Binomial Distributions Binomial Distributions A binomial experiment is a probability experiment that satisfies these conditions. 1. The experiment has a fixed number of trials, where each trial is independent of the other trials.

More information

PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS

PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS I. INTRODUCTION TO RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS A. Random Variables 1. A random variable x represents a value

More information

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin 3 times where P(H) = / (b) THUS, find the probability

More information

Opening Exercise: Lesson 91 - Binomial Distributions IBHL2 - SANTOWSKI

Opening Exercise: Lesson 91 - Binomial Distributions IBHL2 - SANTOWSKI 08-0- Lesson 9 - Binomial Distributions IBHL - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin times where P(H) = / (b) THUS, find the probability

More information

Math Tech IIII, Apr 25

Math Tech IIII, Apr 25 Math Tech IIII, Apr 25 The Binomial Distribution I Book Sections: 4.2 Essential Questions: How can I compute the probability of any event? What is the binomial distribution and how can I use it? Standards:

More information

Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world

Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world Pearson Education Limited Edinburgh Gate Harlow Essex CM0 JE England and Associated Companies throughout the world Visit us on the World Wide Web at: www.pearsoned.co.uk Pearson Education Limited 04 All

More information

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions Random Variables Examples: Random variable a variable (typically represented by x) that takes a numerical value by chance. Number of boys in a randomly selected family with three children. Possible values:

More information

Lecture 6 Probability

Lecture 6 Probability Faculty of Medicine Epidemiology and Biostatistics الوبائيات واإلحصاء الحيوي (31505204) Lecture 6 Probability By Hatim Jaber MD MPH JBCM PhD 3+4-7-2018 1 Presentation outline 3+4-7-2018 Time Introduction-

More information

What is the probability of success? Failure? How could we do this simulation using a random number table?

What is the probability of success? Failure? How could we do this simulation using a random number table? Probability Ch.4, sections 4.2 & 4.3 Binomial and Geometric Distributions Name: Date: Pd: 4.2. What is a binomial distribution? How do we find the probability of success? Suppose you have three daughters.

More information

Chapter 4 Probability Distributions

Chapter 4 Probability Distributions Slide 1 Chapter 4 Probability Distributions Slide 2 4-1 Overview 4-2 Random Variables 4-3 Binomial Probability Distributions 4-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 4-5

More information

Section Introduction to Normal Distributions

Section Introduction to Normal Distributions Section 6.1-6.2 Introduction to Normal Distributions 2012 Pearson Education, Inc. All rights reserved. 1 of 105 Section 6.1-6.2 Objectives Interpret graphs of normal probability distributions Find areas

More information

Chapter 3. Discrete Probability Distributions

Chapter 3. Discrete Probability Distributions Chapter 3 Discrete Probability Distributions 1 Chapter 3 Overview Introduction 3-1 The Binomial Distribution 3-2 Other Types of Distributions 2 Chapter 3 Objectives Find the exact probability for X successes

More information

Chapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1

Chapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Discrete Probability Distributions McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Overview Introduction 5-1 Probability Distributions 5-2 Mean, Variance, Standard Deviation, and Expectation

More information

guessing Bluman, Chapter 5 2

guessing Bluman, Chapter 5 2 Bluman, Chapter 5 1 guessing Suppose there is multiple choice quiz on a subject you don t know anything about. 15 th Century Russian Literature; Nuclear physics etc. You have to guess on every question.

More information

Overview. Definitions. Definitions. Graphs. Chapter 4 Probability Distributions. probability distributions

Overview. Definitions. Definitions. Graphs. Chapter 4 Probability Distributions. probability distributions Chapter 4 Probability Distributions 4-1 Overview 4-2 Random Variables 4-3 Binomial Probability Distributions 4-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 4-5 The Poisson Distribution

More information

The Binomial Probability Distribution

The Binomial Probability Distribution The Binomial Probability Distribution MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives After this lesson we will be able to: determine whether a probability

More information

Math Tech IIII, Mar 6

Math Tech IIII, Mar 6 Math Tech IIII, Mar 6 The Binomial Distribution II Book Sections: 4.2 Essential Questions: How can I compute the probability of any event? What do I need to know about the binomial distribution? Standards:

More information

Math 14 Lecture Notes Ch. 4.3

Math 14 Lecture Notes Ch. 4.3 4.3 The Binomial Distribution Example 1: The former Sacramento King's DeMarcus Cousins makes 77% of his free throws. If he shoots 3 times, what is the probability that he will make exactly 0, 1, 2, or

More information

Part 10: The Binomial Distribution

Part 10: The Binomial Distribution Part 10: The Binomial Distribution The binomial distribution is an important example of a probability distribution for a discrete random variable. It has wide ranging applications. One readily available

More information

Math 160 Professor Busken Chapter 5 Worksheets

Math 160 Professor Busken Chapter 5 Worksheets Math 160 Professor Busken Chapter 5 Worksheets Name: 1. Find the expected value. Suppose you play a Pick 4 Lotto where you pay 50 to select a sequence of four digits, such as 2118. If you select the same

More information

Probability Distributions

Probability Distributions 4.1 Probability Distributions Random Variables A random variable x represents a numerical value associated with each outcome of a probability distribution. A random variable is discrete if it has a finite

More information

The Central Limit Theorem

The Central Limit Theorem Section 6-5 The Central Limit Theorem I. Sampling Distribution of Sample Mean ( ) Eample 1: Population Distribution Table 2 4 6 8 P() 1/4 1/4 1/4 1/4 μ (a) Find the population mean and population standard

More information

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1 Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability

More information

A random variable is a (typically represented by ) that has a. value, determined by, A probability distribution is a that gives the

A random variable is a (typically represented by ) that has a. value, determined by, A probability distribution is a that gives the 5.2 RANDOM VARIABLES A random variable is a (typically represented by ) that has a value, determined by, for each of a. A probability distribution is a that gives the for each value of the. It is often

More information

Random Variables. Chapter 6: Random Variables 2/2/2014. Discrete and Continuous Random Variables. Transforming and Combining Random Variables

Random Variables. Chapter 6: Random Variables 2/2/2014. Discrete and Continuous Random Variables. Transforming and Combining Random Variables Chapter 6: Random Variables Section 6.3 The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Random Variables 6.1 6.2 6.3 Discrete and Continuous Random Variables Transforming and Combining

More information

No, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation.

No, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation. 1) If n 100 and p 0.02 in a binomial experiment, does this satisfy the rule for a normal approximation? Why or why not? No, because np 100(0.02) 2. The value of np must be greater than or equal to 5 to

More information

Discrete Probability Distribution

Discrete Probability Distribution 1 Discrete Probability Distribution Key Definitions Discrete Random Variable: Has a countable number of values. This means that each data point is distinct and separate. Continuous Random Variable: Has

More information

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial Lecture 8 The Binomial Distribution Probability Distributions: Normal and Binomial 1 2 Binomial Distribution >A binomial experiment possesses the following properties. The experiment consists of a fixed

More information

Statistical Methods in Practice STAT/MATH 3379

Statistical Methods in Practice STAT/MATH 3379 Statistical Methods in Practice STAT/MATH 3379 Dr. A. B. W. Manage Associate Professor of Mathematics & Statistics Department of Mathematics & Statistics Sam Houston State University Overview 6.1 Discrete

More information

Midterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary.

Midterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary. MA 180/418 Midterm Test 1 (Sample) Student Name (PRINT):............................................. Student Signature:................................................... Use pencil, so that you can erase

More information

A random variable is a quantitative variable that represents a certain

A random variable is a quantitative variable that represents a certain Section 6.1 Discrete Random Variables Example: Probability Distribution, Spin the Spinners Sum of Numbers on Spinners Theoretical Probability 2 0.04 3 0.08 4 0.12 5 0.16 6 0.20 7 0.16 8 0.12 9 0.08 10

More information

Math Tech IIII, Mar 13

Math Tech IIII, Mar 13 Math Tech IIII, Mar 13 The Binomial Distribution III Book Sections: 4.2 Essential Questions: What do I need to know about the binomial distribution? Standards: DA-5.6 What Makes a Binomial Experiment?

More information

Binomial Distribution. Normal Approximation to the Binomial

Binomial Distribution. Normal Approximation to the Binomial Binomial Distribution Normal Approximation to the Binomial /29 Homework Read Sec 6-6. Discussion Question pg 337 Do Ex 6-6 -4 2 /29 Objectives Objective: Use the normal approximation to calculate 3 /29

More information

CHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS

CHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS CHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS A random variable is the description of the outcome of an experiment in words. The verbal description of a random variable tells you how to find or calculate

More information

STATISTICS GUIDED NOTEBOOK/FOR USE WITH MARIO TRIOLA S TEXTBOOK ESSENTIALS OF STATISTICS, 4TH ED.

STATISTICS GUIDED NOTEBOOK/FOR USE WITH MARIO TRIOLA S TEXTBOOK ESSENTIALS OF STATISTICS, 4TH ED. Example 3: There is a 0.9968 probability that a randomly selected 50-year old female lives through the year (based on data from the U.S. Department of Health and Human Services). A Fidelity life insurance

More information

Chapter 12. Binomial Setting. Binomial Setting Examples

Chapter 12. Binomial Setting. Binomial Setting Examples Chapter 12 Binomial Distributions BPS - 3rd Ed. Chapter 12 1 Binomial Setting Fixed number n of observations The n observations are independent Each observation falls into one of just two categories may

More information

Overview. Definitions. Definitions. Graphs. Chapter 5 Probability Distributions. probability distributions

Overview. Definitions. Definitions. Graphs. Chapter 5 Probability Distributions. probability distributions Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 5-5 The Poisson Distribution

More information

Chapter Five. The Binomial Probability Distribution and Related Topics

Chapter Five. The Binomial Probability Distribution and Related Topics Chapter Five The Binomial Probability Distribution and Related Topics Section 3 Additional Properties of the Binomial Distribution Essential Questions How are the mean and standard deviation determined

More information

MidTerm 1) Find the following (round off to one decimal place):

MidTerm 1) Find the following (round off to one decimal place): MidTerm 1) 68 49 21 55 57 61 70 42 59 50 66 99 Find the following (round off to one decimal place): Mean = 58:083, round off to 58.1 Median = 58 Range = max min = 99 21 = 78 St. Deviation = s = 8:535,

More information

Counting Basics. Venn diagrams

Counting Basics. Venn diagrams Counting Basics Sets Ways of specifying sets Union and intersection Universal set and complements Empty set and disjoint sets Venn diagrams Counting Inclusion-exclusion Multiplication principle Addition

More information

Chpt The Binomial Distribution

Chpt The Binomial Distribution Chpt 5 5-4 The Binomial Distribution 1 /36 Chpt 5-4 Chpt 5 Homework p262 Applying the Concepts Exercises p263 1-11, 14-18, 23, 24, 26 2 /36 Objective Chpt 5 Find the exact probability for x successes in

More information

4.1 Probability Distributions

4.1 Probability Distributions Probability and Statistics Mrs. Leahy Chapter 4: Discrete Probability Distribution ALWAYS KEEP IN MIND: The Probability of an event is ALWAYS between: and!!!! 4.1 Probability Distributions Random Variables

More information

Chapter 5 Probability Distributions. Section 5-2 Random Variables. Random Variable Probability Distribution. Discrete and Continuous Random Variables

Chapter 5 Probability Distributions. Section 5-2 Random Variables. Random Variable Probability Distribution. Discrete and Continuous Random Variables Chapter 5 Probability Distributions Section 5-2 Random Variables 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance and Standard Deviation for the Binomial Distribution Random

More information

CH 5 Normal Probability Distributions Properties of the Normal Distribution

CH 5 Normal Probability Distributions Properties of the Normal Distribution Properties of the Normal Distribution Example A friend that is always late. Let X represent the amount of minutes that pass from the moment you are suppose to meet your friend until the moment your friend

More information

Chapter 3 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.

Chapter 3 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc. 1 3.1 Describing Variation Stem-and-Leaf Display Easy to find percentiles of the data; see page 69 2 Plot of Data in Time Order Marginal plot produced by MINITAB Also called a run chart 3 Histograms Useful

More information

Unit 04 Review. Probability Rules

Unit 04 Review. Probability Rules Unit 04 Review Probability Rules A sample space contains all the possible outcomes observed in a trial of an experiment, a survey, or some random phenomenon. The sum of the probabilities for all possible

More information

Chapter. Discrete Probability Distributions Pearson Pren-ce Hall. All rights reserved

Chapter. Discrete Probability Distributions Pearson Pren-ce Hall. All rights reserved Chapter 36 Discrete Probability Distributions 2010 Pearson Pren-ce Hall. All rights Sec-on 6.1 Probability Rules 2010 Pearson Pren-ce Hall. All rights 6-2 2010 Pearson Pren-ce Hall. All rights 6-3 A random

More information

30 Wyner Statistics Fall 2013

30 Wyner Statistics Fall 2013 30 Wyner Statistics Fall 2013 CHAPTER FIVE: DISCRETE PROBABILITY DISTRIBUTIONS Summary, Terms, and Objectives A probability distribution shows the likelihood of each possible outcome. This chapter deals

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Chapter 6 Exam A Name The given values are discrete. Use the continuity correction and describe the region of the normal distribution that corresponds to the indicated probability. 1) The probability of

More information

. 13. The maximum error (margin of error) of the estimate for μ (based on known σ) is:

. 13. The maximum error (margin of error) of the estimate for μ (based on known σ) is: Statistics Sample Exam 3 Solution Chapters 6 & 7: Normal Probability Distributions & Estimates 1. What percent of normally distributed data value lie within 2 standard deviations to either side of the

More information

Lecture 9. Probability Distributions. Outline. Outline

Lecture 9. Probability Distributions. Outline. Outline Outline Lecture 9 Probability Distributions 6-1 Introduction 6- Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7- Properties of the Normal Distribution

More information

Discrete Probability Distributions

Discrete Probability Distributions Page 1 of 6 Discrete Probability Distributions In order to study inferential statistics, we need to combine the concepts from descriptive statistics and probability. This combination makes up the basics

More information

Chapter Six Probability Distributions

Chapter Six Probability Distributions 6.1 Probability Distributions Discrete Random Variable Chapter Six Probability Distributions x P(x) 2 0.08 4 0.13 6 0.25 8 0.31 10 0.16 12 0.01 Practice. Construct a probability distribution for the number

More information

6.3: The Binomial Model

6.3: The Binomial Model 6.3: The Binomial Model The Normal distribution is a good model for many situations involving a continuous random variable. For experiments involving a discrete random variable, where the outcome of the

More information

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -

More information

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Identify the given random variable as being discrete or continuous. 1) The number of phone

More information

Probability Review. The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE

Probability Review. The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Probability Review The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Probability Models In Section 5.1, we used simulation to imitate chance behavior. Fortunately, we don t have to

More information

Lecture 9. Probability Distributions

Lecture 9. Probability Distributions Lecture 9 Probability Distributions Outline 6-1 Introduction 6-2 Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7-2 Properties of the Normal Distribution

More information

STA258H5. Al Nosedal and Alison Weir. Winter Al Nosedal and Alison Weir STA258H5 Winter / 41

STA258H5. Al Nosedal and Alison Weir. Winter Al Nosedal and Alison Weir STA258H5 Winter / 41 STA258H5 Al Nosedal and Alison Weir Winter 2017 Al Nosedal and Alison Weir STA258H5 Winter 2017 1 / 41 NORMAL APPROXIMATION TO THE BINOMIAL DISTRIBUTION. Al Nosedal and Alison Weir STA258H5 Winter 2017

More information

12 Math Chapter Review April 16 th, Multiple Choice Identify the choice that best completes the statement or answers the question.

12 Math Chapter Review April 16 th, Multiple Choice Identify the choice that best completes the statement or answers the question. Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Which situation does not describe a discrete random variable? A The number of cell phones per household.

More information

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution Section 7.6 Application of the Normal Distribution A random variable that may take on infinitely many values is called a continuous random variable. A continuous probability distribution is defined by

More information

AP Statistics Ch 8 The Binomial and Geometric Distributions

AP Statistics Ch 8 The Binomial and Geometric Distributions Ch 8.1 The Binomial Distributions The Binomial Setting A situation where these four conditions are satisfied is called a binomial setting. 1. Each observation falls into one of just two categories, which

More information

Part 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going?

Part 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going? 1 The Law of Averages The Expected Value & The Standard Error Where Are We Going? Sums of random numbers The law of averages Box models for generating random numbers Sums of draws: the Expected Value Standard

More information

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom Section 5-1 Probability Distributions I. Random Variables A variable x is a if the value that it assumes, corresponding to the of an experiment, is a or event. A random variable is if it potentially can

More information

Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES

Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Essential Question How can I determine whether the conditions for using binomial random variables are met? Binomial Settings When the

More information

II - Probability. Counting Techniques. three rules of counting. 1multiplication rules. 2permutations. 3combinations

II - Probability. Counting Techniques. three rules of counting. 1multiplication rules. 2permutations. 3combinations II - Probability Counting Techniques three rules of counting 1multiplication rules 2permutations 3combinations Section 2 - Probability (1) II - Probability Counting Techniques 1multiplication rules In

More information

Business Statistics. Chapter 5 Discrete Probability Distributions QMIS 120. Dr. Mohammad Zainal

Business Statistics. Chapter 5 Discrete Probability Distributions QMIS 120. Dr. Mohammad Zainal Department of Quantitative Methods & Information Systems Business Statistics Chapter 5 Discrete Probability Distributions QMIS 120 Dr. Mohammad Zainal Chapter Goals After completing this chapter, you should

More information

MATH 264 Problem Homework I

MATH 264 Problem Homework I MATH Problem Homework I Due to December 9, 00@:0 PROBLEMS & SOLUTIONS. A student answers a multiple-choice examination question that offers four possible answers. Suppose that the probability that the

More information

AP Statistics Quiz A Chapter 17

AP Statistics Quiz A Chapter 17 AP Statistics Quiz A Chapter 17 Name The American Red Cross says that about 11% of the U.S. population has Type B blood. A blood drive is being held at your school. 1. How many blood donors should the

More information

Chapter 5 Student Lecture Notes 5-1. Department of Quantitative Methods & Information Systems. Business Statistics

Chapter 5 Student Lecture Notes 5-1. Department of Quantitative Methods & Information Systems. Business Statistics Chapter 5 Student Lecture Notes 5-1 Department of Quantitative Methods & Information Systems Business Statistics Chapter 5 Discrete Probability Distributions QMIS 120 Dr. Mohammad Zainal Chapter Goals

More information

Exercises for Chapter (5)

Exercises for Chapter (5) Exercises for Chapter (5) MULTILE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) 500 families were interviewed and the number of children per family was

More information

STAT Chapter 5: Continuous Distributions. Probability distributions are used a bit differently for continuous r.v. s than for discrete r.v. s.

STAT Chapter 5: Continuous Distributions. Probability distributions are used a bit differently for continuous r.v. s than for discrete r.v. s. STAT 515 -- Chapter 5: Continuous Distributions Probability distributions are used a bit differently for continuous r.v. s than for discrete r.v. s. Continuous distributions typically are represented by

More information

8.1 Binomial Distributions

8.1 Binomial Distributions 8.1 Binomial Distributions The Binomial Setting The 4 Conditions of a Binomial Setting: 1.Each observation falls into 1 of 2 categories ( success or fail ) 2 2.There is a fixed # n of observations. 3.All

More information

x is a random variable which is a numerical description of the outcome of an experiment.

x is a random variable which is a numerical description of the outcome of an experiment. Chapter 5 Discrete Probability Distributions Random Variables is a random variable which is a numerical description of the outcome of an eperiment. Discrete: If the possible values change by steps or jumps.

More information

Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a

Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a Announcements: There are some office hour changes for Nov 5, 8, 9 on website Week 5 quiz begins after class today and ends at

More information

Binomial Random Variables. Binomial Random Variables

Binomial Random Variables. Binomial Random Variables Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering heads as success and tails as

More information

Math 14 Lecture Notes Ch The Normal Approximation to the Binomial Distribution. P (X ) = nc X p X q n X =

Math 14 Lecture Notes Ch The Normal Approximation to the Binomial Distribution. P (X ) = nc X p X q n X = 6.4 The Normal Approximation to the Binomial Distribution Recall from section 6.4 that g A binomial experiment is a experiment that satisfies the following four requirements: 1. Each trial can have only

More information

Example. Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables

Example. Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables You are dealt a hand of 5 cards. Find the probability distribution table for the number of hearts. Graph

More information

7 THE CENTRAL LIMIT THEOREM

7 THE CENTRAL LIMIT THEOREM CHAPTER 7 THE CENTRAL LIMIT THEOREM 373 7 THE CENTRAL LIMIT THEOREM Figure 7.1 If you want to figure out the distribution of the change people carry in their pockets, using the central limit theorem and

More information

Chapter 4 and 5 Note Guide: Probability Distributions

Chapter 4 and 5 Note Guide: Probability Distributions Chapter 4 and 5 Note Guide: Probability Distributions Probability Distributions for a Discrete Random Variable A discrete probability distribution function has two characteristics: Each probability is

More information

This is very simple, just enter the sample into a list in the calculator and go to STAT CALC 1-Var Stats. You will get

This is very simple, just enter the sample into a list in the calculator and go to STAT CALC 1-Var Stats. You will get MATH 111: REVIEW FOR FINAL EXAM SUMMARY STATISTICS Spring 2005 exam: 1(A), 2(E), 3(C), 4(D) Comments: This is very simple, just enter the sample into a list in the calculator and go to STAT CALC 1-Var

More information

CHAPTER 5 Sampling Distributions

CHAPTER 5 Sampling Distributions CHAPTER 5 Sampling Distributions 5.1 The possible values of p^ are 0, 1/3, 2/3, and 1. These correspond to getting 0 persons with lung cancer, 1 with lung cancer, 2 with lung cancer, and all 3 with lung

More information

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution.

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution. MA 5 Lecture - Mean and Standard Deviation for the Binomial Distribution Friday, September 9, 07 Objectives: Mean and standard deviation for the binomial distribution.. Mean and Standard Deviation of the

More information

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table:

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table: Chapter8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number

More information

Math Week in Review #10. Experiments with two outcomes ( success and failure ) are called Bernoulli or binomial trials.

Math Week in Review #10. Experiments with two outcomes ( success and failure ) are called Bernoulli or binomial trials. Math 141 Spring 2006 c Heather Ramsey Page 1 Section 8.4 - Binomial Distribution Math 141 - Week in Review #10 Experiments with two outcomes ( success and failure ) are called Bernoulli or binomial trials.

More information

Problem Set 07 Discrete Random Variables

Problem Set 07 Discrete Random Variables Name Problem Set 07 Discrete Random Variables MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the mean of the random variable. 1) The random

More information

(c) The probability that a randomly selected driver having a California drivers license

(c) The probability that a randomly selected driver having a California drivers license Statistics Test 2 Name: KEY 1 Classify each statement as an example of classical probability, empirical probability, or subjective probability (a An executive for the Krusty-O cereal factory makes an educated

More information

MA131 Lecture 9.1. = µ = 25 and σ X P ( 90 < X < 100 ) = = /// σ X

MA131 Lecture 9.1. = µ = 25 and σ X P ( 90 < X < 100 ) = = /// σ X The Central Limit Theorem (CLT): As the sample size n increases, the shape of the distribution of the sample means taken with replacement from the population with mean µ and standard deviation σ will approach

More information

Chapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc.

Chapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 8 Random Variables Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. 8.1 What is a Random Variable? Random Variable: assigns a number to each outcome of a random circumstance, or,

More information

Econ 6900: Statistical Problems. Instructor: Yogesh Uppal

Econ 6900: Statistical Problems. Instructor: Yogesh Uppal Econ 6900: Statistical Problems Instructor: Yogesh Uppal Email: yuppal@ysu.edu Lecture Slides 4 Random Variables Probability Distributions Discrete Distributions Discrete Uniform Probability Distribution

More information

2011 Pearson Education, Inc

2011 Pearson Education, Inc Statistics for Business and Economics Chapter 4 Random Variables & Probability Distributions Content 1. Two Types of Random Variables 2. Probability Distributions for Discrete Random Variables 3. The Binomial

More information

MA : Introductory Probability

MA : Introductory Probability MA 320-001: Introductory Probability David Murrugarra Department of Mathematics, University of Kentucky http://www.math.uky.edu/~dmu228/ma320/ Spring 2017 David Murrugarra (University of Kentucky) MA 320:

More information

Chapter 8. Binomial and Geometric Distributions

Chapter 8. Binomial and Geometric Distributions Chapter 8 Binomial and Geometric Distributions Lesson 8-1, Part 1 Binomial Distribution What is a Binomial Distribution? Specific type of discrete probability distribution The outcomes belong to two categories

More information

a) Less than 0.66 b) Greater than 0.74 c) Between 0.64 and 0.76

a) Less than 0.66 b) Greater than 0.74 c) Between 0.64 and 0.76 Example #7 According to a National Sleep Foundation Survey, 70% of adults takes more than 30 minutes to fall asleep at night. Assume that this percentage is true for the population of all U.S. adults.

More information

Chapter 7. Sampling Distributions

Chapter 7. Sampling Distributions Chapter 7 Sampling Distributions Section 7.1 Sampling Distributions and the Central Limit Theorem Sampling Distributions Sampling distribution The probability distribution of a sample statistic. Formed

More information

Consider the following examples: ex: let X = tossing a coin three times and counting the number of heads

Consider the following examples: ex: let X = tossing a coin three times and counting the number of heads Overview Both chapters and 6 deal with a similar concept probability distributions. The difference is that chapter concerns itself with discrete probability distribution while chapter 6 covers continuous

More information

Chapter 5. Discrete Probability Distributions. Random Variables

Chapter 5. Discrete Probability Distributions. Random Variables Chapter 5 Discrete Probability Distributions Random Variables x is a random variable which is a numerical description of the outcome of an experiment. Discrete: If the possible values change by steps or

More information