381 Probability-III (Permutations and Combinations) QSCI 381 – Lecture 11 (Larson and Farber, Sect 3.4)

Slides:



Advertisements
Similar presentations
Counting Principles Probability.
Advertisements

10.1 – Counting by Systematic Listing
Probabilities Through Simulations
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
381 Introduction to Probability Distributions QSCI 381 – Lecture 12 (Larson and Farber, Sect 4.1)
Chapter 3 Probability.
Introduction to Probability
How many possible outcomes can you make with the accessories?
Discrete Mathematics Lecture 6 Alexander Bukharovich New York University.
381 Discrete Probability Distributions (The Binomial Distribution) QSCI 381 – Lecture 13 (Larson and Farber, Sect 4.2)
Chapter Probability © 2010 Pearson Prentice Hall. All rights reserved 3 5.
Counting Principles and Probability Digital Lesson.
3.4 Counting Principles Statistics Mrs. Spitz Fall 2008.
Aim: Final Review Session 3 Probability
NA387 Lecture 5: Combinatorics, Conditional Probability
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Counting Section 3-7 M A R I O F. T R I O L A Copyright © 1998, Triola, Elementary.
P ERMUTATIONS AND C OMBINATIONS Homework: Permutation and Combinations WS.
Section 3.3 The Addition Rule.
Chapter 4 Lecture 4 Section: 4.7. Counting Fundamental Rule of Counting: If an event occurs m ways and if a different event occurs n ways, then the events.
DISCRETE PROBABILITY DISTRIBUTIONS
Section 3.3 The Addition Rule.
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.
10.3 – Using Permutations and Combinations Permutation: The number of ways in which a subset of objects can be selected from a given set of objects, where.
IT College Introduction to Computer Statistical Packages Lecture 9 Eng. Heba Hamad 2010.
Section 10-3 Using Permutations and Combinations.
Probability Chapter 3. § 3.4 Counting Principles.
© The McGraw-Hill Companies, Inc., Chapter 4 Counting Techniques.
Basic Probability Permutations and Combinations: -Combinations: -The number of different packages of data taken r at time from a data set containing n.
Part 2 – Factorial and other Counting Rules
Statistics 1: Elementary Statistics Section 4-7. Probability Chapter 3 –Section 2: Fundamentals –Section 3: Addition Rule –Section 4: Multiplication Rule.
Probability Counting Methods. Do Now: Find the probablity of: Rolling a 4 on a die Rolling a “hard eight” (2 - 4’s) on a pair of dice.
Introduction to Probability. 5.1 Experiments, Outcomes, Events, and Sample Spaces Sample space - The set of all possible outcomes for an experiment Roll.
10/23/ Combinations. 10/23/ Combinations Remember that Permutations told us how many different ways we could choose r items from a group.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Sullivan Algebra and Trigonometry: Section 14.2 Objectives of this Section Solve Counting Problems Using the Multiplication Principle Solve Counting Problems.
Introduction to Counting Methods, Fundamental Counting Principal, and Permutations and Combinations.
3.4 Counting Principles I.The Fundamental Counting Principle: if one event can occur m ways and a second event can occur n ways, the number of ways the.
Chapter 4 Lecture 4 Section: 4.7. Counting Fundamental Rule of Counting: If an event occurs m ways and if a different event occurs n ways, then the events.
Aim: What is the counting rule? Exam Tomorrow. Three Rules Sometimes we need to know all possible outcomes for a sequence of events – We use three rules.
381 Probability-II (The Rules of Probability & Counting Rules) QSCI 381 – Lecture 8 (Larson and Farber, Sects )
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Counting Techniques Tree Diagram Multiplication Rule Permutations Combinations.
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
Probability. 3.1 Events, Sample Spaces, and Probability Sample space - The set of all possible outcomes for an experiment Roll a die Flip a coin Measure.
Permutations and Combinations
Special Topics. Calculating Outcomes for Equally Likely Events If a random phenomenon has equally likely outcomes, then the probability of event A is:
Probability and Counting Rules 4-4: Counting Rules.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Counting Introduction to Probability & Statistics Counting.
Introduction to probability (2) Combinations التوافيق Definition of combination: It is a way of selecting items from a collection, such that the order.
CHAPTER 4 4-4:Counting Rules Instructor: Alaa saud Note: This PowerPoint is only a summary and your main source should be the book.
1 2.3 Counting Sample Points (6)(6)(6)= 216 Example: How many outcome sequences are possible when a die is rolled three times?
Permutations and Combinations. Fundamental Counting Principle Fundamental Counting Principle states that if an event has m possible outcomes and another.
13 Lesson 1 Let Me Count the Ways Fundamental Counting Principle, Permutations & Combinations CP Probability and Statistics FA 2014 S-ID.1S-CP.3S-CP.5.
Chapter 10 Counting Methods.
Elementary Probability Theory
Permutations and Combinations
Do Now If fours cards are drawn from a deck without replacement, find the probability of getting these results: All kings All diamonds All sevens.
Testing for Independence
Permutations and Combinations
How many possible outcomes can you make with the accessories?
Permutations.
Counting Methods and Probability Theory
Using Permutations and Combinations
Counting Methods and Probability Theory
Permutations and Combinations
10.3 – Using Permutations and Combinations
Presentation transcript:

381 Probability-III (Permutations and Combinations) QSCI 381 – Lecture 11 (Larson and Farber, Sect 3.4)

381 Permutations-I A is an ordered arrangement of objects. The number of different arrangements (permutations) of n different objects is n! (n-factorial). Key note: We are interested in the order of things.

381 3! = 3 x 2 x 1 = Permutations-I

381 Permutations-II The number of permutations of n distinct objects taken r (r <n) at a time is: Returning to our earlier example; selecting 4 of 10 animals to age. Here n=10 and r=4 so

381 There are forty-three republican candidates hoping to be in the top three candidates at each primary election. In each state, how many ways can the candidates finish first, second, and third? n P r = 43 P 3 = 43!/(43-3)! = 43!/40! = 43 x 42 x 41 74,046 primary standing options Permutations-II

381 Permutations-III The number of of n objects when n 1 are of one type, n 2 are of another type, etc. is: = 6!/(3! x 2! X 1!) = (6 x 5 x 4)/(2 x 1) = 120/2 = 60

381 Permutations-III (Example) You have five sockeye, four pink and four chum salmon. How many ways can they be arranged?

381 Permutations-III (Example) You have five sockeye, four pink and four chum salmon. How many ways can they be arranged?

381 Combinations-I A is a selection of r objects from a group of n objects without regard to order and is denoted by. The number of combinations of r objects selected from a group of n objects is: Key note: We are not interested in the order of things.

381 Combinations-II Example. We have fish from three species (A, B, C) and wish to select two of them. How many ways can we do this: (A,B), (B,C), (A,C). 3 C 2 =3 It is not (A,B),(B,C),(A,C),(B,A),(C,B),(C,A) Because order does not count. 3!/(3-2)!2! = 6/2 = 3

381 Combinations-III (Example) You wish to test the impact of five treatments. However, your experiment can only consider three treatments at once. How many experiments do you need to conduct so that all combinations of the three treatments are examined? Hint: after the lecture write down all the combinations after naming them A, B, C, D, E.

381 Combinations -IV The number of combinations of r objects chosen from n distinct objects allowing for repetitions is:

381 Combinations vs Permutations-I Permutations relate to the number of ways of selecting r objects from n when the order of the items matters. Combinations relate to the number of ways of selecting r objects from n when the order does not matter.

381 Combinations vs Permutations-II Without repetition With repetition Permutations Combinations

381 Relationship to Probability-I If there are n people together - what is the probability that all have different birthdays: Total number of permutations of birthdays: 365 n (fundamental counting rule 365x365…) Number of ways that n people can have different birthdays: 365 P n =365!/(365-n)! For n=23, the ratio 365 P 23 / = Permutation without repetition

381 More on Birthdays and Probability Number of people

381 Relationship to Probability-II A subgroup of four people is selected at random from a group of 5 married couples. What is the probability that the selection consists of two married couples: Number of ways of selecting 4 people from 10 is: 10!/(6!.4!) Number of ways of selecting 2 couples from 5 couples is : 5!/(3!.2!) The ratio of these is Combination without repetition

381 Relationship to Probability-III There are 33 candidates in an election to a Committee of 3. What is the probability that Smith, Jones and Williams are elected (assume that elections are random): We are interested in one combination of all possible combinations. There 33 C 3 combinations of 3 selected from 33 so the probability 1/ 33 C 3 = Hint. The factorial function in EXCEL is “Fact(x)” and there are also functions “Combin(A,B)” and “Permut(A,B)”.

381 Relationship to Probability-IV An experiment involves three counting devices. Each has a probability of failure of What is the probability that one fails? What is the probability that none fails? What is the probability at least two don’t fail?

381 Common Mistakes Assuming probabilities have a memory: You toss a (fair) coin and get eight heads – what was the probability of this and what is the probability of an eight head? Adding probabilities incorrectly. Why is the probability of surveying a pregnant female bowhead whale not 0.7 if the probability of encountering a female is 0.5 and 20% of the population is pregnant?