Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved 3 5.

Slides:



Advertisements
Similar presentations
Counting Principles Probability.
Advertisements

Permutations and Combinations
Modular 9 Ch 5.4 to 5.5 Copyright of the definitions and examples is reserved to Pearson Education, Inc.. In order to use this PowerPoint presentation,
Copyright © Cengage Learning. All rights reserved. 7 Probability.
Warm-Up Problem Can you predict which offers more choices for license plates? Choice A: a plate with three different letters of the alphabet in any order.
Decisions, Decisions, Decisions
Chapter 3 Probability.
4/2/03Tucker, Section 5.31 How many ways to arrange the six letters b, a, n, a, n, a ? Arrangements and Selections With Repetitions Six places: __ __ __.
Section 4-7 Counting.
Counting Principles and Probability Digital Lesson.
Logic and Introduction to Sets Chapter 6 Dr.Hayk Melikyan/ Department of Mathematics and CS/ For more complicated problems, we will.
College Algebra Fifth Edition
Probability Chapter 3. § 3.1 Basic Concepts of Probability.
Chapter 5 Section 5 Counting Techniques.
5.5 Counting Techniques. More Challenging Stuff  The classical method, when all outcomes are equally likely, involves counting the number of ways something.
4. Counting 4.1 The Basic of Counting Basic Counting Principles Example 1 suppose that either a member of the faculty or a student in the department is.
Chapter 7 Logic, Sets, and Counting Section 4 Permutations and Combinations.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 11 Counting Methods and Probability Theory.
6.4 Permutations and combinations For more complicated problems, we will need to develop two important concepts: permutations and combinations. Both of.
NA387 Lecture 5: Combinatorics, Conditional Probability
Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
Dr. Fowler AFM Unit 7-7 Permutations and Combinations.
Section 7.1. Section Summary Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning.
PROBABILITY. Counting methods can be used to find the number of possible ways to choose objects with and without regard to order. The Fundamental Counting.
Chapter 7 With Question/Answer Animations. Section 7.1.
1 Combinations. 2 Permutations-Recall from yesterday The number of possible arrangements (order matters) of a specific size from a group of objects is.
Advanced Precalculus Advanced Precalculus Notes 12.2 Permutations and Combinations.
Slide Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
March 10, 2015Applied Discrete Mathematics Week 6: Counting 1 Permutations and Combinations How many different sets of 3 people can we pick from a group.
Section 5.5 Counting Techniques. An airport shuttle bus driver needs to pick up 4 separate passengers: a,b,c,d. How many different ways can the.
Section 15.3 – Day 2 Counting. When do I use what? Rearranging things that are all different: Counting Principles (multiplication), Combinations, Permutations.
Probability Chapter 3. § 3.4 Counting Principles.
Lesson Counting Techniques. Objectives Solve counting problems using the Multiplication Rule Solve counting problems using permutations Solve counting.
Aim: How do we use permutation and combination to evaluate probability? Do Now: Your investment counselor has placed before you a portfolio of 6 stocks.
Objectives Solve counting problems using the Multiplication Rule Solve counting problems using permutations Solve counting problems using combinations.
Prob/Stats Definition A permutation is an ordered arrangement of objects. (For example, consider the permutations of the letters A, B, C and D.)
Copyright © 2011 Pearson Education, Inc. Publishing as Prentice Hall.
Chapter 7 Logic, Sets, and Counting Section 4 Permutations and Combinations.
Sullivan Algebra and Trigonometry: Section 14.2 Objectives of this Section Solve Counting Problems Using the Multiplication Principle Solve Counting Problems.
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Learning Objectives for Section 7.4 Permutations and Combinations The student will be able to set up and.
Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved 3 5.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Probability 5.
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Probability
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 11 Counting Methods and Probability Theory.
HAWKES LEARNING Students Count. Success Matters. Copyright © 2015 by Hawkes Learning/Quant Systems, Inc. All rights reserved. Section 7.2 Counting Our.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 11 Counting Methods and Probability Theory.
COUNTING Permutations and Combinations. 2Barnett/Ziegler/Byleen College Mathematics 12e Learning Objectives for Permutations and Combinations  The student.
Special Topics. Calculating Outcomes for Equally Likely Events If a random phenomenon has equally likely outcomes, then the probability of event A is:
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Probability 5.
© 2010 Pearson Prentice Hall. All rights reserved. 1 §11.5, Probability with the Fundamental Counting Principle, Permutations, and Combinations.
Counting Techniques Section 5.5. Objectives Solve counting problems using the Multiplication Rule Solve counting problems using permutations Solve counting.
Combinatorial Principles, Permutations, and Combinations
addition and multiplication
12.2 Permutations and Combinations
Chapter 5 Probability 5.5 Counting Techniques.
Chapter 0.4 Counting Techniques.
3 5 Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved.
Elementary Statistics
How to Count Things “There are three kinds of people in the world: those who can count and those who cannot.” 11/21/2018.
4 Probability Lesson 4.8 Combinations and Probability.
Chapter 7 Logic, Sets, and Counting
Chapter 3 Probability.
Counting Methods and Probability Theory
3 5 Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved.
Counting Methods and Probability Theory
PERMUTATIONS.
STATISTICS INFORMED DECISIONS USING DATA
Presentation transcript:

Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved 3 5

Section 5.5 Counting Techniques 5-2 © 2010 Pearson Prentice Hall. All rights reserved

5-3 © 2010 Pearson Prentice Hall. All rights reserved

5-4 © 2010 Pearson Prentice Hall. All rights reserved

5-5 © 2010 Pearson Prentice Hall. All rights reserved For each choice of appetizer, we have 4 choices of entrée, and that, for each of these 2 4 = 8 choices, there are 2 choices for dessert. A total of = 16 different meals can be ordered. EXAMPLE Counting the Number of Possible Meals

5-6 © 2010 Pearson Prentice Hall. All rights reserved

5-7 © 2010 Pearson Prentice Hall. All rights reserved

5-8 © 2010 Pearson Prentice Hall. All rights reserved A permutation is an ordered arrangement in which r objects are chosen from n distinct (different) objects and repetition is not allowed. The symbol n P r represents the number of permutations of r objects selected from n objects.

5-9 © 2010 Pearson Prentice Hall. All rights reserved

5-10 © 2010 Pearson Prentice Hall. All rights reserved In how many ways can horses in a 10-horse race finish first, second, and third? EXAMPLE Betting on the Trifecta The 10 horses are distinct. Once a horse crosses the finish line, that horse will not cross the finish line again, and, in a race, order is important. We have a permutation of 10 objects taken 3 at a time. The top three horses can finish a 10-horse race in

5-11 © 2010 Pearson Prentice Hall. All rights reserved

5-12 © 2010 Pearson Prentice Hall. All rights reserved A combination is a collection, without regard to order, of n distinct objects without repetition. The symbol n C r represents the number of combinations of n distinct objects taken r at a time.

5-13 © 2010 Pearson Prentice Hall. All rights reserved

5-14 © 2010 Pearson Prentice Hall. All rights reserved How many different simple random samples of size 4 can be obtained from a population whose size is 20? EXAMPLE Simple Random Samples The 20 individuals in the population are distinct. In addition, the order in which individuals are selected is unimportant. Thus, the number of simple random samples of size 4 from a population of size 20 is a combination of 20 objects taken 4 at a time. Use Formula (2) with n = 20 and r = 4: There are 4,845 different simple random samples of size 4 from a population whose size is 20.

5-15 © 2010 Pearson Prentice Hall. All rights reserved

5-16 © 2010 Pearson Prentice Hall. All rights reserved

5-17 © 2010 Pearson Prentice Hall. All rights reserved How many different vertical arrangements are there of 10 flags if 5 are white, 3 are blue, and 2 are red? EXAMPLE Arranging Flags We seek the number of permutations of 10 objects, of which 5 are of one kind (white), 3 are of a second kind (blue), and 2 are of a third kind (red). Using Formula (3), we find that there are different vertical arrangements

5-18 © 2010 Pearson Prentice Hall. All rights reserved

5-19 © 2010 Pearson Prentice Hall. All rights reserved In the Illinois Lottery, an urn contains balls numbered 1 to 52. From this urn, six balls are randomly chosen without replacement. For a $1 bet, a player chooses two sets of six numbers. To win, all six numbers must match those chosen from the urn. The order in which the balls are selected does not matter. What is the probability of winning the lottery? EXAMPLE Winning the Lottery The probability of winning is given by the number of ways a ticket could win divided by the size of the sample space. Each ticket has two sets of six numbers, so there are two chances of winning for each ticket. The sample space S is the number of ways that 6 objects can be selected from 52 objects without replacement and without regard to order, so N(S) = 52 C 6.

5-20 © 2010 Pearson Prentice Hall. All rights reserved The size of the sample space is EXAMPLE Winning the Lottery Each ticket has two sets of 6 numbers, so a player has two chances of winning for52 6each $1. If E is the event “winning ticket,” then N1E2 = 2 There is about a 1 in 10,000,000 chance of winning the Illinois Lottery!