Week 10 - Monday.  What did we talk about last time?  Combinations  Binomial theorem.

Slides:



Advertisements
Similar presentations
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Advertisements

Chapter 2 Probability. 2.1 Sample Spaces and Events.
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
1 1 PRESENTED BY E. G. GASCON Introduction to Probability Section 7.3, 7.4, 7.5.
8.7 Probability. Ex 1 Find the sample space for each of the following. One coin is tossed. Two coins are tossed. Three coins are tossed.
Chapter 7 Probability 7.1 Experiments, Sample Spaces, and Events
Probability Of An Event Dhon G. Dungca, M.Eng’g..
Discrete Structures Chapter 5 Pigeonhole Principle Nurul Amelina Nasharuddin Multimedia Department.
Discrete Mathematics Lecture 7 Harper Langston New York University.
Chapter 6 Probabilit y Vocabulary Probability – the proportion of times the outcome would occur in a very long series of repetitions (likelihood of an.
Lecture II.  Using the example from Birenens Chapter 1: Assume we are interested in the game Texas lotto (similar to Florida lotto).  In this game,
Week 10 - Monday.  What did we talk about last time?  More permutations  Addition rule  Inclusion and exclusion.
Refreshing Your Skills for Chapter 10.  If you flip a coin, the probability that it lands with heads up is 1/2.  If you roll a standard die, the probability.
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 2 Probability.
Fall 2015 COMP 2300 Discrete Structures for Computation
12.4 Probability of Compound Events
Lecture Discrete Probability. 5.1 Probabilities Important in study of complexity of algorithms. Modeling the uncertain world: information, data.
PROBABILITY AND STATISTICS FOR ENGINEERING Hossein Sameti Department of Computer Engineering Sharif University of Technology Independence and Bernoulli.
Compound Probability Pre-AP Geometry. Compound Events are made up of two or more simple events. I. Compound Events may be: A) Independent events - when.
Section 2 Probability Rules – Compound Events Compound Event – an event that is expressed in terms of, or as a combination of, other events Events A.
Discrete Mathematical Structures (Counting Principles)
1 Copyright © Cengage Learning. All rights reserved. 4 Probability.
Week 15 - Wednesday.  What did we talk about last time?  Review first third of course.
STAT 211 – 019 Dan Piett West Virginia University Lecture 3.
Chapter 1:Independent and Dependent Events
Page 973, 10.3, % 9.43% % 11. Permutation 12. Permutation 13. Combination 14. Combination, 18%
Week 7 - Friday.  What did we talk about last time?  Set disproofs  Russell’s paradox  Function basics.
Week 11 - Wednesday.  What did we talk about last time?  Exam 2 post-mortem  Combinations.
Lesson 6 – 2b Probability Models Part II. Knowledge Objectives Explain what is meant by random phenomenon. Explain what it means to say that the idea.
Mutually Exclusive Events OBJ: Find the probability that mutually exclusive and inclusive events occur.
Computing Fundamentals 2 Lecture 6 Probability Lecturer: Patrick Browne
Week 11 - Monday.  What did we talk about last time?  Binomial theorem and Pascal's triangle  Conditional probability  Bayes’ theorem.
1 CHAPTERS 14 AND 15 (Intro Stats – 3 edition) PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY.
Copyright © 2010 Pearson Education, Inc. Chapter 6 Probability.
Algebra II 10.4: Find Probabilities of Disjoint and Overlapping Events HW: HW: p.710 (8 – 38 even) Chapter 10 Test: Thursday.
Chapter 4 Probability. Definitions A probability experiment is a chance process that leads to well-defined results called outcomes. An outcome is the.
Probability Section 7.1. What is probability? Probability discusses the likelihood or chance of something happening. For instance, -- the probability.
1 CHAPTER 7 PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY.
Probability Basic Concepts Start with the Monty Hall puzzle
Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
ICS 253: Discrete Structures I Discrete Probability King Fahd University of Petroleum & Minerals Information & Computer Science Department.
Sixth lecture Concepts of Probabilities. Random Experiment Can be repeated (theoretically) an infinite number of times Has a well-defined set of possible.
Introduction to Probability (Dr. Monticino). Assignment Sheet  Read Chapters 13 and 14  Assignment #8 (Due Wednesday March 23 rd )  Chapter 13  Exercise.
SECTION 11-2 Events Involving “Not” and “Or” Slide
Independent Events Lesson Starter State in writing whether each of these pairs of events are disjoint. Justify your answer. If the events.
Probability. What is probability? Probability discusses the likelihood or chance of something happening. For instance, -- the probability of it raining.
Probability Bingo October 3, D Mathematics.
Single Pick Probability AND vs. OR Sequential Probability With Replacement Conditional Disjoint vs. Non Disjoint Unit 4 – Probability – Part 1.
5-Minute Check on Section 6-2a Click the mouse button or press the Space Bar to display the answers. 1.If you have a choice from 6 shirts, 5 pants, 10.
Chapter 10 – Data Analysis and Probability 10.7 – Probability of Compound Events.
Single Pick Probability AND vs. OR Sequential Probability With Replacement Conditional Disjoint vs. Non Disjoint Unit 4 – Probability – Part 1.
Unit 4 Probability Day 3: Independent and Dependent events.
Pigeonhole Principle. If n pigeons fly into m pigeonholes and n > m, then at least one hole must contain two or more pigeons A function from one finite.
Week 15 - Wednesday.  What did we talk about last time?  Review first third of course.
Week 10 - Wednesday.  What did we talk about last time?  Counting practice  Pigeonhole principle.
Probability What is the probability of rolling “snake eyes” in one roll? What is the probability of rolling “yahtzee” in one roll?
Week 9 - Friday.  What did we talk about last time?  Permutations  Counting elements in sets  Brief introduction to combinations.
Samples spaces are _______________
Mathematics Department
Virtual University of Pakistan
ICS 253: Discrete Structures I
The Pigeonhole Principle
Chapter 11 Probability.
Chapter 7: Counting Principles
Good afternoon! August 9, 2017.
Combination and Permutations Quiz!
Click the mouse button or press the Space Bar to display the answers.
Pencil, red pen, highlighter, GP notebook, textbook, calculator
Additional Rule of Probability
Lecture 2 Basic Concepts on Probability (Section 0.2)
Presentation transcript:

Week 10 - Monday

 What did we talk about last time?  Combinations  Binomial theorem

 A bundle of 120 wires has been laid underground between two telephone exchanges 10 miles apart  Unfortunately, it was discovered that the individual wires are not labeled  Visually, there is no way of knowing which wire is which, making connections at either end impossible  Your job is to label the wires at both ends  Walking is your only transportation  You have a battery and a light bulb to test continuity  You have tape and a pen for labeling the wires  What is the shortest distance in miles you will need to walk to correctly identify and label each wire?

 Consider the numbers 1 through 99,999 in their ordinary decimal representations.  How many contain exactly one of each of the digits 2, 3, 4, and 5?  For example, 53,142 counts but 53,541 does not

 On an 8 × 8 chessboard, a rook is allowed to move any number of squares either horizontally or vertically.  How many different paths can a rook follow from the bottom-left square of the board to the top-right square of the board if all moves are to the right or upward?  Hint: Think of representing each move as an R or a U

 A bakery produces six different kinds of pastry, one of which is eclairs. Assume there are at least 20 pastries of each kind.  How many different selections of twenty pastries are there?  How many different selections of twenty pastries are there if at least three must be eclairs?  How many different selections of twenty pastries contain at most two eclairs?

 How many different solutions are there to the following equation, assuming that each x i is a nonnegative integer? x 1 + x 2 + x 3 = 20  What if each x i is a positive integer?

 a + b is called a binomial  Using combinations (or Pascal's Triangle) it is easy to compute (a + b) n

 Compute (2x + 3) 7 using the binomial theorem

Student Lecture

 If n pigeons fly into m pigeonholes, where n > m, then there is at least one pigeonhole with two or more pigeons in it  More formally, if a function has a larger domain than co-domain, it cannot be one-to-one  We cannot say exactly how many pigeons are in any given holes  Some holes may be empty  But, at least one hole will have at least two pigeons

 A sock drawer has white socks, black socks, and red argyle socks, all mixed together,  What is the smallest number of socks you need to pull out to be guaranteed a matching pair?  Let A = {1, 2, 3, 4, 5, 6, 7, 8}  If you select five distinct elements from A, must it be the case that some pair of integers from the five you selected will sum to 9?

 If n pigeons fly into m pigeonholes, and for some positive integer k, n > km, then at least one pigeonhole contains k + 1 or more pigeons in it  Example:  In a group of 85 people, at least 4 must have the same last initial

 Let A and B be events in the sample space S  0 ≤ P(A) ≤ 1  P(  ) = 0 and P(S) = 1  If A  B = , then P(A  B) = P(A) + P(B)  It is clear then that P(A c ) = 1 – P(A)  More generally, P(A  B) = P(A) + P(B) – P(A  B)  All of these axioms can be derived from set theory and the definition of probability

 What is the probability that a card drawn randomly from an Anglo-American 52 card deck is a face card (jack, queen, or king) or is red (hearts or diamonds)?  Hint:  Compute the probability that it is a face card  Compute the probability that it is red  Compute the probability that it is both

 Expected value is one of the most important concepts in probability, especially if you want to gamble  The expected value is simply the sum of all events, weighted by their probabilities  If you have n outcomes with real number values a 1, a 2, a 3, … a n, each of which has probability p 1, p 2, p 3, … p n, then the expected value is:

 A normal American roulette wheel has 38 numbers: 1 through 36, 0, and 00  18 numbers are red, 18 numbers are black, and 0 and 00 are green  The best strategy you can have is always betting on black (or red)  If you bet $1 on black and win, you get $1, but you lose your dollar if it lands red  What is the expected value of a bet?

 Given that some event A has happened, the probability that some event B will happen is called conditional probability  This probability is:

 Given two, fair, 6-sided dice, what is the probability that the sum of the numbers they show when rolled is 8, given that both of the numbers are even?

 Let sample space S be a union of mutually disjoint events B 1, B 2, B 3, … B n  Let A be an event in S  Let A and B 1 through B n have non-zero probabilities  For B k where 1 ≤ k ≤ n

 Bayes' theorem is often used to evaluate tests that can have false positives and false negatives  Consider a test for a disease that 1 in 5000 people have  The false positive rate is 3%  The false negative rate is 1%  What's the probability that a person who tests positive for the disease has the disease?  Let A be the event that the person tests positively for the disease  Let B 1 be the event that the person actually has the disease  Let B 2 be the event that the person does not have the disease  Apply Bayes' theorem

 If events A and B are events in a sample space S, then these events are independent if and only if P(A  B) = P(A)∙P(B)  This should be clear from conditional probability  If A and B are independent, then P(B|A) = P(B)

 Finish probability  Graph basics

 Finish reading Chapter 9  Work on Homework 8  Due next Friday  Start reading Chapter 10