Introduction to Probability. 5.1 Experiments, Outcomes, Events, and Sample Spaces Sample space - The set of all possible outcomes for an experiment Roll.

Slides:



Advertisements
Similar presentations
Probability: The Study of Randomness
Advertisements

Introduction to Probability Experiments, Outcomes, Events and Sample Spaces What is probability? Basic Rules of Probability Probabilities of Compound Events.
Probability Simple Events
Chapter 2 Probability. 2.1 Sample Spaces and Events.
Copyright ©2011 Nelson Education Limited. Probability and Probability Distributions CHAPTER 4.
Chapter 4 Probability and Probability Distributions
Probability Chapter 3. Methods of Counting  The type of counting important for probability theory involves choosing the number of ways we can arrange.
Sets: Reminder Set S – sample space - includes all possible outcomes
Chapter 4 Introduction to Probability
Chapter 4 Introduction to Probability
Chapter 3 Probability.
Introduction to Probability
4.2 Probability Models. We call a phenomenon random if individual outcomes are uncertain but there is nonetheless a regular distribution of outcomes in.
Elementary Probability Theory
Probability Concepts Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
CHAPTER 5 PROBABILITY. CARDS & DICE BLACKRED CLUBSPADEDIAMONDHEARTTOTAL ACE11114 FACE CARD (K, Q, J) NUMBERED CARD (1-9) TOTAL13 52.
Probability Chapter 3. § 3.1 Basic Concepts of Probability.
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 2 Probability.
Chapter 4 Probability See.
Overview 5.1 Introducing Probability 5.2 Combining Events
Elementary Probability Theory
Chapter 4 Probability 4-1 Overview 4-2 Fundamentals 4-3 Addition Rule
5.1 Basic Probability Ideas
10/1/20151 Math a Sample Space, Events, and Probabilities of Events.
EGR Sample Space, S The set of all possible outcomes of an experiment. Each outcome is an element or member or sample point. If the set is finite.
Math 409/409G History of Mathematics
1 Probability. 2 Today’s plan Probability Notations Laws of probability.
AP Statistics Chapter 6 Notes. Probability Terms Random: Individual outcomes are uncertain, but there is a predictable distribution of outcomes in the.
Unit 3 Review. Sec 5.1: Designing Samples Define the terms population and sample. Define each type of sample: Probability Sample, Simple Random Sample.
Chapter 8: Probability: The Mathematics of Chance Lesson Plan Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Continuous.
Section 2.6: Probability and Expectation Practice HW (not to hand in) From Barr Text p. 130 # 1, 2, 4-12.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
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.
Chapter 4 Probability ©. Sample Space sample space.S The possible outcomes of a random experiment are called the basic outcomes, and the set of all basic.
Week 11 What is Probability? Quantification of uncertainty. Mathematical model for things that occur randomly. Random – not haphazard, don’t know what.
1 Chapter 4 – Probability An Introduction. 2 Chapter Outline – Part 1  Experiments, Counting Rules, and Assigning Probabilities  Events and Their Probability.
Probability is a measure of the likelihood of a random phenomenon or chance behavior. Probability describes the long-term proportion with which a certain.
5.1 Randomness  The Language of Probability  Thinking about Randomness  The Uses of Probability 1.
From Randomness to Probability Chapter 14. Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes could happen,
Probability Basic Concepts Start with the Monty Hall puzzle
Chapter 8: Probability: The Mathematics of Chance Lesson Plan Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Continuous.
Introduction to Probability (Dr. Monticino). Assignment Sheet  Read Chapters 13 and 14  Assignment #8 (Due Wednesday March 23 rd )  Chapter 13  Exercise.
Chapter 4 Probability, Randomness, and Uncertainty.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
Chapter 3:Basic Probability Concepts Probability: is a measure (or number) used to measure the chance of the occurrence of some event. This number is between.
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.
Probability. Randomness When we produce data by randomized procedures, the laws of probability answer the question, “What would happen if we did this.
Chapter 8: Probability: The Mathematics of Chance Lesson Plan Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Continuous.
Counting Techniques (Dr. Monticino). Overview  Why counting?  Counting techniques  Multiplication principle  Permutation  Combination  Examples.
Welcome to MM207 Unit 3 Seminar Dr. Bob Probability and Excel 1.
Probability Probability II. Opening Routine # 1.
Probability Models Section 6.2. The Language of Probability What is random? What is random? Empirical means that it is based on observation rather than.
Section Probability Models AP Statistics December 2, 2010.
PROBABILITY AND STATISTICS WEEK 2 Onur Doğan. Introduction to Probability The Classical Interpretation of Probability The Frequency Interpretation of.
Math a - Sample Space - Events - Definition of Probabilities
Elementary Probability Theory
Unit 8 Probability.
Chapter 4 Probability Concepts
Chapter 6 6.1/6.2 Probability Probability is the branch of mathematics that describes the pattern of chance outcomes.
STATISTICS AND PROBABILITY IN CIVIL ENGINEERING
PROBABILITY AND PROBABILITY RULES
Probability.
Basic Concepts An experiment is the process by which an observation (or measurement) is obtained. An event is an outcome of an experiment,
PROBABILITY AND STATISTICS
Chapter 3 Probability.
Unit 1: Basic Probability
Mr. Reider AP Stat November 18, 2010
Presentation transcript:

Introduction to Probability

5.1 Experiments, Outcomes, Events, and Sample Spaces Sample space - The set of all possible outcomes for an experiment Roll a die Flip a coin Measure heights

Some experiments consist of a series of operations. A device called a tree diagram is useful for determining the sample space. Example: Flip a Penny, Nickel, and a Dime Event - Any subset of the sample space An event is said to occur when any outcome in the event occurs

5.2 Assigning Probabilities to Events The probability of an event A, denoted, is the expected proportion of occurrences of A if the experiment were performed a large number of times. When outcomes are equally likely Examples: Flip a fair coin Roll a balanced die

When probability is based on frequencies Example: Results of sample Males (event M) – 40 Females (event F) – 60

5.3 Some Basic Rules of Probability The closer to 1 a probability the more likely the event

5.4 Probabilities of Compound Events The complement of an event A, denoted or, is all sample points not in A. The complement rule: Joint Probability – an event that has two or more characteristics

The union of two events, denoted, is the event composed of outcomes from A or B. In other words, if A occurs, B occurs, or both A and B occur, then it is said that occurred. The intersection of two events, denoted, is the event composed of outcomes from A and B. In other words, if both A and B occur, then it is said that occurred.

5.5 Conditional Probability Sometimes we wish to know if event A occurred given that we know that event B occurred. This is known as conditional probability, denoted A|B. Example Roll a balanced green die and a balanced red die Denote outcomes by (G,R)

Red Die Green Die (1,1)(2,1)(3,1)(4,1)(5,1)(6,1) 2(1,2)(2,2)(3,2)(4,2)(5,2)(6,2) 3(1,3)(2,3)(3,3)(4,3)(5,3)(6,3) 4(1,4)(2,4)(3,4)(4,4)(5,4)(6,4) 5(1,5)(2,5)(3,5)(4,5)(5,5)(6,5) 6(1,6)(2,6)(3,6)(4,6)(5,6)(6,6)

We say the events A and B are mutually exclusive or disjoint if they cannot occur together The addition rule The conditional probability of A given B is

Example: Select an individual at random from a population of drivers classified by gender number of traffic tickets 0 tickets1 ticket2 tickets3 or more ticketsTotal Female Male Total

5.6 Independence Two events are said to be independent if the occurrence (or nonoccurrence) of one does not effect the probability of occurrence of the other. Events that are not independent are dependent.

Example: Draw two cards without replacement Multiplication rule: Suppose we return the first card thoroughly shuffle before we draw the second

Example Select an individual at random Ask place of residence & Do you favor combining city and county governments Favor (F)OpposeTotal City (C) Outside Total

5.8 Counting Techniques How many different ways are there to arrange the 6 letters in the word SUNDAY? Suppose you have a lock with a three digit code. Each digit is a number 0 through 9. How many possible codes are there?

The symbol, read as “n factorial” is defined as and so on

Evaluate each expression

Permutations Ordered arrangements of distinct objects are called permutations. (order matters) If we wish to know the number of r permutations of n distinct objects, it is denoted as In how many ways can you select a president, vice president, treasurer, and secretary from a group of 10?

Combinations Unordered selections of distinct objects are called combinations. (order does not matter) If we wish to know the number of r combinations of n distinct objects, it is denoted as In how many ways can a committee of 5 senators be selected from a group of 8 senators?