Counting & Basic probabilities. Stat 430 Heike Hofmann
|
|
- Bertha Berry
- 5 years ago
- Views:
Transcription
1 Counting & Basic probabilities Stat 430 Heike Hofmann 1
2 Outline Combinatorics (Counting rules) Conditional probability Bayes rule 2
3 Combinatorics 3
4 Summation Principle Alternative Choices Start n1 ways n2 ways... nk ways Stop If a complex action can be performed using k alternative methods and each method can be done in n 1,n 2,...,n k ways, there are a total of N ways that the complex action can be performed, with N = n 1 + n n k 4
5 Multiplication Principle Sequence of Choices Start n1 ways n2 ways... nk ways Stop If a complex action consists of a series of k actions and each action can be done in n 1,n 2,...,n k ways, there are a total of N ways that the complex action can be performed, with N = n 1 n 2... n k 5
6 Counting Examples roll two dice Ω 1 = (1, 1), (1, 2)... (1, 6) (2, 1), (2, 2)... (2, 6) (6, 1), (6, 2)... (6, 6) 6
7 e.g. roll two dice (1, 1), (1, 2)... (1, 6) (2, 1), (2, 2)... (2, 6) Ω 1 = (6, 1), (6, 2)... (6, 6) Ω 2 = {1, 1}, {1, 2}... {1, 6} {2, 2}... {2, 6}.... {6, 6} 7
8 e.g. roll two dice (1, 1), (1, 2)... (1, 6) (2, 1), (2, 2)... (2, 6) Ω 1 = (6, 1), (6, 2)... (6, 6) 36 elements Ω 2 = {1, 1}, {1, 2}... {1, 6} {2, 2}... {2, 6}.... {6, 6} 7
9 e.g. roll two dice (1, 1), (1, 2)... (1, 6) (2, 1), (2, 2)... (2, 6) Ω 1 = (6, 1), (6, 2)... (6, 6) 36 elements Ω 2 = {1, 1}, {1, 2}... {1, 6} {2, 2}... {2, 6}.... {6, 6} 21 elements 7
10 e.g. roll two dice (1, 1), (1, 2)... (1, 6) (2, 1), (2, 2)... (2, 6) Ω 1 = (6, 1), (6, 2)... (6, 6) order matters Ω 2 = order does not matter {1, 1}, {1, 2}... {1, 6} {2, 2}... {2, 6}.... {6, 6} 36 elements 21 elements 7
11 e.g. roll three dice order matters order does not matter 8
12 e.g. roll three dice order matters Ω 1 =6 6 6 = 216 elements order does not matter Ω 2 =... = 55 elements 8
13 pick four cards from stack of 52 order matters order does not matter 9
14 pick four cards from stack of 52 order matters Ω 1 = = choices order does not matter Ω 2 = 52 = elements 9
15 Difference between dice & cards example die results are always in {1, 2, 3, 4, 5, 6} (with replacement) once a card is drawn, it is out of the stack (without replacement) 10
16 Counting Rules Goal: determine overall size of sample space without listing all elements manually Side benefit: usually we can find a mathematical description of the sample space in the process. 11
17 Combinatorics 12
18 Counting rules Urn model n numbered objects (balls) in a bag (urn)
19 Ordered samples with replacement Urn model: pick ball from urn, write down number, put ball back,repeat k times Sequential setup fits Multiplication principle: N = n n... n = n k k times 14
20 Ordered samples without replacement Urn model: pick ball from urn, write down number, put ball not back,repeat k times Sequential k times setup fits Multiplication principle: N = n (n 1)... (n k + 1) k times = n! (n k)! 15
21 Ordered samples without replacement Urn model: pick ball from urn, write down number, put ball not back,repeat k times Sequential k times setup fits Multiplication principle: N = n (n 1)... (n k + 1) k times this is also called the permutation number = n! (n k)! 15
22 Unordered samples without replacement Urn model: pick k balls from urn at once Trick: pick balls ordered w/o replacement, then mes remove order: n! N = (n k)! n! n (k!) 1 = (n k)!k! = k 16
23 Unordered samples with replacement Urn model: pick ball from urn, write down number, put ball back,repeat k times, keep only record of #times each ball is sampled: k balls, (n-1) lines, i.e. k+n-1 objects Trick: place k balls among k+n-1 places n + k 1 N = k 17
24 Example How many ways are there to uniquely rearrange the letters of M I S S I S S I P P I 18
25 Independence 19
26 Probability concepts Independence/Dependency If occurrence of event A changes the probability of event B, the events are dependent: P (B A) = if P(A) 0 P (A B) P (A) 20
27 Independence Events A and B are independent, if P (A B) =P (A) P (B) 21
28 System reliability Serial System: system works, if all of its components are working Parallel System: system works if at least one component is working 22
29 Bayes Rule 23
30 Bayes Rule Definition: cover A set of events B 1,B 2,B 3,... is a cover, if the sets are pairwise disjoint and exhaustive (i.e. they cover the sample space) 24
31 Bayes Rule Total probability Let B 1,B 2,B 3,... be a cover of the sample space, then P(A) can be computed as k P (A) = P (B i ) P (A B i ). i=1 25
32 Bayes Theorem Let space, then B 1,B 2,B 3,... P (B j A) = P (B j A) P (A) Bayes Rule = be a cover of the sample P (A B j ) P (B j ) k i=1 P (A B i) P (B i ) 26
Compound Probability. Set Theory. Basic Definitions
Compound Probability Set Theory A probability measure P is a function that maps subsets of the state space Ω to numbers in the interval [0, 1]. In order to study these functions, we need to know some basic
More informationIf a regular six-sided die is rolled, the possible outcomes can be listed as {1, 2, 3, 4, 5, 6} there are 6 outcomes.
Section 11.1: The Counting Principle 1. Combinatorics is the study of counting the different outcomes of some task. For example If a coin is flipped, the side facing upward will be a head or a tail the
More informationNovember 6, Chapter 8: Probability: The Mathematics of Chance
Chapter 8: Probability: The Mathematics of Chance November 6, 2013 Last Time Crystallographic notation Groups Crystallographic notation The first symbol is always a p, which indicates that the pattern
More informationCS 237: Probability in Computing
CS 237: Probability in Computing Wayne Snyder Computer Science Department Boston University Lecture 5: o Independence reviewed; Bayes' Rule o Counting principles and combinatorics; o Counting considered
More informationSTAT 3743: Probability and Statistics
STAT 3743: Probability and Statistics G. Jay Kerns, Youngstown State University Fall 2010 Probability Random experiment: outcome not known in advance Sample space: set of all possible outcomes (S) Probability
More informationElementary Combinatorics
184 DISCRETE MATHEMATICAL STRUCTURES 7 Elementary Combinatorics 7.1 INTRODUCTION Combinatorics deals with counting and enumeration of specified objects, patterns or designs. Techniques of counting are
More informationContents 2.1 Basic Concepts of Probability Methods of Assigning Probabilities Principle of Counting - Permutation and Combination 39
CHAPTER 2 PROBABILITY Contents 2.1 Basic Concepts of Probability 38 2.2 Probability of an Event 39 2.3 Methods of Assigning Probabilities 39 2.4 Principle of Counting - Permutation and Combination 39 2.5
More informationProblems from 9th edition of Probability and Statistical Inference by Hogg, Tanis and Zimmerman:
Math 22 Fall 2017 Homework 2 Drew Armstrong Problems from 9th edition of Probability and Statistical Inference by Hogg, Tanis and Zimmerman: Section 1.2, Exercises 5, 7, 13, 16. Section 1.3, Exercises,
More informationBlock 1 - Sets and Basic Combinatorics. Main Topics in Block 1:
Block 1 - Sets and Basic Combinatorics Main Topics in Block 1: A short revision of some set theory Sets and subsets. Venn diagrams to represent sets. Describing sets using rules of inclusion. Set operations.
More informationCounting and Probability
Counting and Probability What s to come? Probability. A bag contains: What is the chance that a ball taken from the bag is blue? Count blue. Count total. Divide. Today: Counting! Later this week: Probability.
More informationNovember 11, Chapter 8: Probability: The Mathematics of Chance
Chapter 8: Probability: The Mathematics of Chance November 11, 2013 Last Time Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Probability Rules Probability Rules Rule 1.
More information2. Combinatorics: the systematic study of counting. The Basic Principle of Counting (BPC)
2. Combinatorics: the systematic study of counting The Basic Principle of Counting (BPC) Suppose r experiments will be performed. The 1st has n 1 possible outcomes, for each of these outcomes there are
More informationCS 361: Probability & Statistics
February 7, 2018 CS 361: Probability & Statistics Independence & conditional probability Recall the definition for independence So we can suppose events are independent and compute probabilities Or we
More informationThe study of probability is concerned with the likelihood of events occurring. Many situations can be analyzed using a simplified model of probability
The study of probability is concerned with the likelihood of events occurring Like combinatorics, the origins of probability theory can be traced back to the study of gambling games Still a popular branch
More informationDiscrete mathematics
Discrete mathematics Petr Kovář petr.kovar@vsb.cz VŠB Technical University of Ostrava DiM 470-2301/02, Winter term 2018/2019 About this file This file is meant to be a guideline for the lecturer. Many
More informationCSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability (solutions)
CSE 31: Foundations of Computing II Quiz Section #: Inclusion-Exclusion, Pigeonhole, Introduction to Probability (solutions) Review: Main Theorems and Concepts Binomial Theorem: x, y R, n N: (x + y) n
More informationProbability Rules 3.3 & 3.4. Cathy Poliak, Ph.D. (Department of Mathematics 3.3 & 3.4 University of Houston )
Probability Rules 3.3 & 3.4 Cathy Poliak, Ph.D. cathy@math.uh.edu Department of Mathematics University of Houston Lecture 3: 3339 Lecture 3: 3339 1 / 23 Outline 1 Probability 2 Probability Rules Lecture
More informationProbability (Devore Chapter Two)
Probability (Devore Chapter Two) 1016-351-01 Probability Winter 2011-2012 Contents 1 Axiomatic Probability 2 1.1 Outcomes and Events............................... 2 1.2 Rules of Probability................................
More informationLesson 3 Dependent and Independent Events
Lesson 3 Dependent and Independent Events When working with 2 separate events, we must first consider if the first event affects the second event. Situation 1 Situation 2 Drawing two cards from a deck
More informationTEST A CHAPTER 11, PROBABILITY
TEST A CHAPTER 11, PROBABILITY 1. Two fair dice are rolled. Find the probability that the sum turning up is 9, given that the first die turns up an even number. 2. Two fair dice are rolled. Find the probability
More informationMathematical Foundations HW 5 By 11:59pm, 12 Dec, 2015
1 Probability Axioms Let A,B,C be three arbitrary events. Find the probability of exactly one of these events occuring. Sample space S: {ABC, AB, AC, BC, A, B, C, }, and S = 8. P(A or B or C) = 3 8. note:
More informationProbability MAT230. Fall Discrete Mathematics. MAT230 (Discrete Math) Probability Fall / 37
Probability MAT230 Discrete Mathematics Fall 2018 MAT230 (Discrete Math) Probability Fall 2018 1 / 37 Outline 1 Discrete Probability 2 Sum and Product Rules for Probability 3 Expected Value MAT230 (Discrete
More informationSample Spaces, Events, Probability
Sample Spaces, Events, Probability CS 3130/ECE 3530: Probability and Statistics for Engineers August 28, 2014 Sets A set is a collection of unique objects. Sets A set is a collection of unique objects.
More informationNovember 8, Chapter 8: Probability: The Mathematics of Chance
Chapter 8: Probability: The Mathematics of Chance November 8, 2013 Last Time Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Crystallographic notation The first symbol
More informationLecture 14. What s to come? Probability. A bag contains:
Lecture 14 What s to come? Probability. A bag contains: What is the chance that a ball taken from the bag is blue? Count blue. Count total. Divide. Today: Counting! Later: Probability. Professor Walrand.
More informationDiscrete Structures for Computer Science
Discrete Structures for Computer Science William Garrison bill@cs.pitt.edu 6311 Sennott Square Lecture #23: Discrete Probability Based on materials developed by Dr. Adam Lee The study of probability is
More informationChapter 1. Probability
Chapter 1. Probability 1.1 Basic Concepts Scientific method a. For a given problem, we define measures that explains the problem well. b. Data is collected with observation and the measures are calculated.
More informationRANDOM EXPERIMENTS AND EVENTS
Random Experiments and Events 18 RANDOM EXPERIMENTS AND EVENTS In day-to-day life we see that before commencement of a cricket match two captains go for a toss. Tossing of a coin is an activity and getting
More informationChapter 1. Probability
Chapter 1. Probability 1.1 Basic Concepts Scientific method a. For a given problem, we define measures that explains the problem well. b. Data is collected with observation and the measures are calculated.
More informationProbability Theory. Mohamed I. Riffi. Islamic University of Gaza
Probability Theory Mohamed I. Riffi Islamic University of Gaza Table of contents 1. Chapter 1 Probability Properties of probability Counting techniques 1 Chapter 1 Probability Probability Theorem P(φ)
More informationQ1) 6 boys and 6 girls are seated in a row. What is the probability that all the 6 gurls are together.
Required Probability = where Q1) 6 boys and 6 girls are seated in a row. What is the probability that all the 6 gurls are together. Solution: As girls are always together so they are considered as a group.
More informationSection Summary. Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning
Section 7.1 Section Summary Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning Probability of an Event Pierre-Simon Laplace (1749-1827) We first study Pierre-Simon
More informationUnit 6: Probability. Marius Ionescu 10/06/2011. Marius Ionescu () Unit 6: Probability 10/06/ / 22
Unit 6: Probability Marius Ionescu 10/06/2011 Marius Ionescu () Unit 6: Probability 10/06/2011 1 / 22 Chapter 13: What is a probability Denition The probability that an event happens is the percentage
More informationToday s Topics. Next week: Conditional Probability
Today s Topics 2 Last time: Combinations Permutations Group Assignment TODAY: Probability! Sample Spaces and Event Spaces Axioms of Probability Lots of Examples Next week: Conditional Probability Sets
More informationUnit 6: Probability. Marius Ionescu 10/06/2011. Marius Ionescu () Unit 6: Probability 10/06/ / 22
Unit 6: Probability Marius Ionescu 10/06/2011 Marius Ionescu () Unit 6: Probability 10/06/2011 1 / 22 Chapter 13: What is a probability Denition The probability that an event happens is the percentage
More informationBIOL2300 Biostatistics Chapter 4 Counting and Probability
BIOL2300 Biostatistics Chapter 4 Counting and Probability Event, sample space sample space (generally denoted Ω, pronounced omega ): set of outcomes of a random experiment {H,T} set of coin flips {1,2,3,4,5,6}
More information1. Counting. 2. Tree 3. Rules of Counting 4. Sample with/without replacement where order does/doesn t matter.
Lecture 4 Outline: basics What s to come? Probability A bag contains: What is the chance that a ball taken from the bag is blue? Count blue Count total Divide Today: Counting! Later: Probability Professor
More informationINDEPENDENT AND DEPENDENT EVENTS UNIT 6: PROBABILITY DAY 2
INDEPENDENT AND DEPENDENT EVENTS UNIT 6: PROBABILITY DAY 2 WARM UP Students in a mathematics class pick a card from a standard deck of 52 cards, record the suit, and return the card to the deck. The results
More informationCSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability
CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability Review: Main Theorems and Concepts Binomial Theorem: Principle of Inclusion-Exclusion
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Study Guide for Test III (MATH 1630) Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the number of subsets of the set. 1) {x x is an even
More informationIndependent Events. 1. Given that the second baby is a girl, what is the. e.g. 2 The probability of bearing a boy baby is 2
Independent Events 7. Introduction Consider the following examples e.g. E throw a die twice A first thrown is "" second thrown is "" o find P( A) Solution: Since the occurrence of Udoes not dependu on
More informationGrade 7/8 Math Circles February 25/26, Probability
Faculty of Mathematics Waterloo, Ontario N2L 3G1 Probability Grade 7/8 Math Circles February 25/26, 2014 Probability Centre for Education in Mathematics and Computing Probability is the study of how likely
More informationSection Introduction to Sets
Section 1.1 - Introduction to Sets Definition: A set is a well-defined collection of objects usually denoted by uppercase letters. Definition: The elements, or members, of a set are denoted by lowercase
More informationTextbook: pp Chapter 2: Probability Concepts and Applications
1 Textbook: pp. 39-80 Chapter 2: Probability Concepts and Applications 2 Learning Objectives After completing this chapter, students will be able to: Understand the basic foundations of probability analysis.
More informationDiscrete Mathematics with Applications MATH236
Discrete Mathematics with Applications MATH236 Dr. Hung P. Tong-Viet School of Mathematics, Statistics and Computer Science University of KwaZulu-Natal Pietermaritzburg Campus Semester 1, 2013 Tong-Viet
More information3 The multiplication rule/miscellaneous counting problems
Practice for Exam 1 1 Axioms of probability, disjoint and independent events 1 Suppose P (A 0, P (B 05 (a If A and B are independent, what is P (A B? What is P (A B? (b If A and B are disjoint, what is
More informationCSC/MATA67 Tutorial, Week 12
CSC/MATA67 Tutorial, Week 12 November 23, 2017 1 More counting problems A class consists of 15 students of whom 5 are prefects. Q: How many committees of 8 can be formed if each consists of a) exactly
More informationCHAPTER 2 PROBABILITY. 2.1 Sample Space. 2.2 Events
CHAPTER 2 PROBABILITY 2.1 Sample Space A probability model consists of the sample space and the way to assign probabilities. Sample space & sample point The sample space S, is the set of all possible outcomes
More informationPROBABILITY. 1. Introduction. Candidates should able to:
PROBABILITY Candidates should able to: evaluate probabilities in simple cases by means of enumeration of equiprobable elementary events (e.g for the total score when two fair dice are thrown), or by calculation
More informationSTAT 430/510 Probability Lecture 1: Counting-1
STAT 430/510 Probability Lecture 1: Counting-1 Pengyuan (Penelope) Wang May 22, 2011 Introduction In the early days, probability was associated with games of chance, such as gambling. Probability is describing
More informationMATHEMATICS 152, FALL 2004 METHODS OF DISCRETE MATHEMATICS Outline #10 (Sets and Probability)
MATHEMATICS 152, FALL 2004 METHODS OF DISCRETE MATHEMATICS Outline #10 (Sets and Probability) Last modified: November 10, 2004 This follows very closely Apostol, Chapter 13, the course pack. Attachments
More information3 The multiplication rule/miscellaneous counting problems
Practice for Exam 1 1 Axioms of probability, disjoint and independent events 1. Suppose P (A) = 0.4, P (B) = 0.5. (a) If A and B are independent, what is P (A B)? What is P (A B)? (b) If A and B are disjoint,
More information3. Discrete Probability. CSE 312 Spring 2015 W.L. Ruzzo
3. Discrete Probability CSE 312 Spring 2015 W.L. Ruzzo 2 Probability theory: an aberration of the intellect and ignorance coined into science John Stuart Mill 3 sample spaces Sample space: S is a set of
More informationIntroduction to Probability and Statistics I Lecture 7 and 8
Introduction to Probability and Statistics I Lecture 7 and 8 Basic Probability and Counting Methods Computing theoretical probabilities:counting methods Great for gambling! Fun to compute! If outcomes
More information4.3 Some Rules of Probability
4.3 Some Rules of Probability Tom Lewis Fall Term 2009 Tom Lewis () 4.3 Some Rules of Probability Fall Term 2009 1 / 6 Outline 1 The addition rule 2 The complement rule 3 The inclusion/exclusion principle
More informationCombinatorics: The Fine Art of Counting
Combinatorics: The Fine Art of Counting Week 6 Lecture Notes Discrete Probability Note Binomial coefficients are written horizontally. The symbol ~ is used to mean approximately equal. Introduction and
More informationProbability and Randomness. Day 1
Probability and Randomness Day 1 Randomness and Probability The mathematics of chance is called. The probability of any outcome of a chance process is a number between that describes the proportion of
More informationA Probability Work Sheet
A Probability Work Sheet October 19, 2006 Introduction: Rolling a Die Suppose Geoff is given a fair six-sided die, which he rolls. What are the chances he rolls a six? In order to solve this problem, we
More informationThe Classification of Quadratic Rook Polynomials of a Generalized Three Dimensional Board
Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 3 (2017), pp. 1091-1101 Research India Publications http://www.ripublication.com The Classification of Quadratic Rook Polynomials
More informationName Date. Sample Spaces and Probability For use with Exploration 12.1
. Sample Spaces and Probability For use with Exploration. Essential Question How can you list the possible outcomes in the sample space of an experiment? The sample space of an experiment is the set of
More informationDefine and Diagram Outcomes (Subsets) of the Sample Space (Universal Set)
12.3 and 12.4 Notes Geometry 1 Diagramming the Sample Space using Venn Diagrams A sample space represents all things that could occur for a given event. In set theory language this would be known as the
More informationProbability. Dr. Zhang Fordham Univ.
Probability! Dr. Zhang Fordham Univ. 1 Probability: outline Introduction! Experiment, event, sample space! Probability of events! Calculate Probability! Through counting! Sum rule and general sum rule!
More informationWeek 3 Classical Probability, Part I
Week 3 Classical Probability, Part I Week 3 Objectives Proper understanding of common statistical practices such as confidence intervals and hypothesis testing requires some familiarity with probability
More informationChapter 2: Probability
Chapter 2: Probability Curtis Miller 2018-06-13 Introduction Next we focus on probability. Probability is the mathematical study of randomness and uncertain outcomes. The subject may be as old as calculus.
More informationSTAT 311 (Spring 2016) Worksheet: W3W: Independence due: Mon. 2/1
Name: Group 1. For all groups. It is important that you understand the difference between independence and disjoint events. For each of the following situations, provide and example that is not in the
More informationM146 - Chapter 5 Handouts. Chapter 5
Chapter 5 Objectives of chapter: Understand probability values. Know how to determine probability values. Use rules of counting. Section 5-1 Probability Rules What is probability? It s the of the occurrence
More informationChapter 16. Probability. For important terms and definitions refer NCERT text book. (6) NCERT text book page 386 question no.
Chapter 16 Probability For important terms and definitions refer NCERT text book. Type- I Concept : sample space (1)NCERT text book page 386 question no. 1 (*) (2) NCERT text book page 386 question no.
More informationn! = n(n 1)(n 2) 3 2 1
A Counting A.1 First principles If the sample space Ω is finite and the outomes are equally likely, then the probability measure is given by P(E) = E / Ω where E denotes the number of outcomes in the event
More informationSTANDARD COMPETENCY : 1. To use the statistics rules, the rules of counting, and the characteristic of probability in problem solving.
Worksheet 4 th Topic : PROBABILITY TIME : 4 X 45 minutes STANDARD COMPETENCY : 1. To use the statistics rules, the rules of counting, and the characteristic of probability in problem solving. BASIC COMPETENCY:
More informationMixed Counting Problems
We have studied a number of counting principles and techniques since the beginning of the course and when we tackle a counting problem, we may have to use one or a combination of these principles. The
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
6. Practice Problems Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the probability. ) A bag contains red marbles, blue marbles, and 8
More informationCS 361: Probability & Statistics
January 31, 2018 CS 361: Probability & Statistics Probability Probability theory Probability Reasoning about uncertain situations with formal models Allows us to compute probabilities Experiments will
More informationCS70: Lecture Review. 2. Stars/Bars. 3. Balls in Bins. 4. Addition Rules. 5. Combinatorial Proofs. 6. Inclusion/Exclusion
CS70: Lecture 18. 1. Review. 2. Stars/Bars. 3. Balls in Bins. 4. Addition Rules. 5. Combinatorial Proofs. 6. Inclusion/Exclusion The rules! First rule: n 1 n 2 n 3. Product Rule. k Samples with replacement
More informationProbability. March 06, J. Boulton MDM 4U1. P(A) = n(a) n(s) Introductory Probability
Most people think they understand odds and probability. Do you? Decision 1: Pick a card Decision 2: Switch or don't Outcomes: Make a tree diagram Do you think you understand probability? Probability Write
More informationChapter 4 Student Lecture Notes 4-1
Chapter 4 Student Lecture Notes 4-1 Basic Business Statistics (9 th Edition) Chapter 4 Basic Probability 2004 Prentice-Hall, Inc. Chap 4-1 Chapter Topics Basic Probability Concepts Sample spaces and events,
More informationName: Class: Date: ID: A
Class: Date: Chapter 0 review. A lunch menu consists of different kinds of sandwiches, different kinds of soup, and 6 different drinks. How many choices are there for ordering a sandwich, a bowl of soup,
More information1 of 5 7/16/2009 6:57 AM Virtual Laboratories > 13. Games of Chance > 1 2 3 4 5 6 7 8 9 10 11 3. Simple Dice Games In this section, we will analyze several simple games played with dice--poker dice, chuck-a-luck,
More informationMath 1324 Finite Mathematics Sections 8.2 and 8.3 Conditional Probability, Independent Events, and Bayes Theorem
Finite Mathematics Sections 8.2 and 8.3 Conditional Probability, Independent Events, and Bayes Theorem What is conditional probability? It is where you know some information, but not enough to get a complete
More informationSTAT 515 fa 2016 Lec 04 Independence, Counting Rules
STAT 515 fa 2016 Lec 04 Independence, Counting Rules Karl B. Gregory Friday, August 26th Contents 1 Basic Probability cont. 1 1.1 Independent events (3.6 McCS13).................. 1 1.2 Counting rules
More informationABC High School, Kathmandu, Nepal. Topic : Probability
BC High School, athmandu, Nepal Topic : Probability Grade 0 Teacher: Shyam Prasad charya. Objective of the Module: t the end of this lesson, students will be able to define and say formula of. define Mutually
More informationToss two coins 60 times. Record the number of heads in each trial, in a table.
Coin Experiment When we toss a coin in the air, we expect it to finish on a head or tail with equal likelihood. What to do: Toss one coin 40 times. ecord the number of heads in each trial, in a table:
More informationThe next several lectures will be concerned with probability theory. We will aim to make sense of statements such as the following:
CS 70 Discrete Mathematics for CS Fall 2004 Rao Lecture 14 Introduction to Probability The next several lectures will be concerned with probability theory. We will aim to make sense of statements such
More informationProbability and Statistics. Copyright Cengage Learning. All rights reserved.
Probability and Statistics Copyright Cengage Learning. All rights reserved. 14.2 Probability Copyright Cengage Learning. All rights reserved. Objectives What Is Probability? Calculating Probability by
More information5 Elementary Probability Theory
5 Elementary Probability Theory 5.1 What is Probability? The Basics We begin by defining some terms. Random Experiment: any activity with a random (unpredictable) result that can be measured. Trial: one
More informationApplied Statistics I
Applied Statistics I Liang Zhang Department of Mathematics, University of Utah June 12, 2008 Liang Zhang (UofU) Applied Statistics I June 12, 2008 1 / 29 In Probability, our main focus is to determine
More informationECON 214 Elements of Statistics for Economists
ECON 214 Elements of Statistics for Economists Session 4 Probability Lecturer: Dr. Bernardin Senadza, Dept. of Economics Contact Information: bsenadza@ug.edu.gh College of Education School of Continuing
More informationCombinatorics and Intuitive Probability
Chapter Combinatorics and Intuitive Probability The simplest probabilistic scenario is perhaps one where the set of possible outcomes is finite and these outcomes are all equally likely. A subset of the
More informationCounting Techniques, Combinations, Permutations, Sets and Venn Diagrams
Counting Techniques, Combinations, Permutations, Sets and Venn Diagrams Sections 2.1 & 2.2 Cathy Poliak, Ph.D. cathy@math.uh.edu Office hours: T Th 2:30 pm - 5:45 pm 620 PGH Department of Mathematics University
More informationToss two coins 10 times. Record the number of heads in each trial, in a table.
Coin Experiment When we toss a coin in the air, we expect it to finish on a head or tail with equal likelihood. What to do: Toss one coin 20 times. ecord the number of heads in each trial, in a table:
More informationLecture 1. Permutations and combinations, Pascal s triangle, learning to count
18.440: Lecture 1 Permutations and combinations, Pascal s triangle, learning to count Scott Sheffield MIT 1 Outline Remark, just for fun Permutations Counting tricks Binomial coefficients Problems 2 Outline
More informationThe probability set-up
CHAPTER 2 The probability set-up 2.1. Introduction and basic theory We will have a sample space, denoted S (sometimes Ω) that consists of all possible outcomes. For example, if we roll two dice, the sample
More informationHonors Precalculus Chapter 9 Summary Basic Combinatorics
Honors Precalculus Chapter 9 Summary Basic Combinatorics A. Factorial: n! means 0! = Why? B. Counting principle: 1. How many different ways can a license plate be formed a) if 7 letters are used and each
More informationPROBABILITY. The sample space of the experiment of tossing two coins is given by
PROBABILITY Introduction Probability is defined as a quantitative measure of uncertainty a numerical value that conveys the strength of our belief in the occurrence of an event. The probability of an event
More informationDiscrete Finite Probability Probability 1
Discrete Finite Probability Probability 1 In these notes, I will consider only the finite discrete case. That is, in every situation the possible outcomes are all distinct cases, which can be modeled by
More informationSTAT 430/510 Probability
STAT 430/510 Probability Hui Nie Lecture 1 May 26th, 2009 Introduction Probability is the study of randomness and uncertainty. In the early days, probability was associated with games of chance, such as
More informationPROBABILITY. Example 1 The probability of choosing a heart from a deck of cards is given by
Classical Definition of Probability PROBABILITY Probability is the measure of how likely an event is. An experiment is a situation involving chance or probability that leads to results called outcomes.
More informationProbability. The MEnTe Program Math Enrichment through Technology. Title V East Los Angeles College
Probability The MEnTe Program Math Enrichment through Technology Title V East Los Angeles College 2003 East Los Angeles College. All rights reserved. Topics Introduction Empirical Probability Theoretical
More information23 Applications of Probability to Combinatorics
November 17, 2017 23 Applications of Probability to Combinatorics William T. Trotter trotter@math.gatech.edu Foreword Disclaimer Many of our examples will deal with games of chance and the notion of gambling.
More informationIntroductory Probability
Introductory Probability Combinations Nicholas Nguyen nicholas.nguyen@uky.edu Department of Mathematics UK Agenda Assigning Objects to Identical Positions Denitions Committee Card Hands Coin Toss Counts
More informationTO EARN ANY CREDIT, YOU MUST SHOW WORK.
Prof. Israel N. Nwaguru MATH 4 CHAPTER 8 - REVIEW WORK OUT EACH PROBLEM NEATLY AND ORDERLY BY SHOWING ALL THE STEPS AS INDICATED IN CLASS ON SEPARATE SHEET, THEN CHOSE THE BEST ANSWER. TO EARN ANY CREDIT,
More information