Basic Probability Sets, Subsets Sample Space Event, E Probability of an Event, P(E) How Probabilities are assigned Properties of Probabilities.

Slides:



Advertisements
Similar presentations
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Advertisements

Introduction to Probability Experiments, Outcomes, Events and Sample Spaces What is probability? Basic Rules of Probability Probabilities of Compound Events.
Probability.
Week 21 Basic Set Theory A set is a collection of elements. Use capital letters, A, B, C to denotes sets and small letters a 1, a 2, … to denote the elements.
Sets: Reminder Set S – sample space - includes all possible outcomes
Chris Morgan, MATH G160 January 9, 2012 Lecture 1 Chapter 4.1, 4.2, & 4.3: Set Theory, Introduction to Probability.
Basic Probability. Theoretical versus Empirical Theoretical probabilities are those that can be determined purely on formal or logical grounds, independent.
Math 310 Section 7.1 Probability. What is a probability? Def. In common usage, the word "probability" is used to mean the chance that a particular event.
1 Definitions Experiment – a process by which an observation ( or measurement ) is observed Sample Space (S)- The set of all possible outcomes (or results)
Chapter 4: Probability (Cont.) In this handout: Venn diagrams Event relations Laws of probability Conditional probability Independence of events.
1 Definitions Experiment – a process by which an observation ( or measurement ) is observed Sample Space (S)- The set of all possible outcomes (or results)
Chapter 2 Chapter The sample space of an experiment, denoted S , is the set of all possible outcomes of that experiment. An event is any collection.
Conditional Probability
Venn Diagrams and Probability Target Goals: I can use a Venn diagram to model a chance process of two events. I can use the general addition rule. 5.2b.
Lecture 7 Dustin Lueker.  Experiment ◦ Any activity from which an outcome, measurement, or other such result is obtained  Random (or Chance) Experiment.
Basic Concepts and Approaches
Chapter 9 Introducing Probability - A bridge from Descriptive Statistics to Inferential Statistics.
MATH 3033 based on Dekking et al. A Modern Introduction to Probability and Statistics Slides by Tim Birbeck Instructor Longin Jan Latecki C2: Outcomes,
Chapter 1 Probability and Distributions Math 6203 Fall 2009 Instructor: Ayona Chatterjee.
Probability. An experiment is any process that allows researchers to obtain observations and which leads to a single outcome which cannot be predicted.
Chapter 11 Probability Sample spaces, events, probabilities, conditional probabilities, independence, Bayes’ formula.
College Algebra Sixth Edition James Stewart Lothar Redlin Saleem Watson.
CIS 2033 based on Dekking et al. A Modern Introduction to Probability and Statistics Instructor Longin Jan Latecki C2: Outcomes, events, and probability.
LECTURE 15 THURSDAY, 15 OCTOBER STA 291 Fall
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.
Week 11 What is Probability? Quantification of uncertainty. Mathematical model for things that occur randomly. Random – not haphazard, don’t know what.
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
1 CHAPTERS 14 AND 15 (Intro Stats – 3 edition) PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY.
Project 1 Lecture Notes. Table of Contents Basic Probability Word Processing Mathematics Summation Notation Expected Value Database Functions and Filtering.
Slide 1 © 2002 McGraw-Hill Australia, PPTs t/a Introductory Mathematics & Statistics for Business 4e by John S. Croucher 1 n Learning Objectives –Understand.
The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Chapter 2. Foundations of Probability Section 2.2. Sample Space and Events Jiaping Wang Department of Mathematical.
PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY
From Randomness to Probability Chapter 14. Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes could happen,
확률및공학통계 (Probability and Engineering Statistics) 이시웅.
Basic Principles (continuation) 1. A Quantitative Measure of Information As we already have realized, when a statistical experiment has n eqiuprobable.
Chapter 4, continued.... III. Events and their Probabilities An event is a collection of sample points. The probability of any one event is equal to the.
Discrete Structures By: Tony Thi By: Tony Thi Aaron Morales Aaron Morales CS 490 CS 490.
Probability: Terminology  Sample Space  Set of all possible outcomes of a random experiment.  Random Experiment  Any activity resulting in uncertain.
Probability Definition : The probability of a given event is an expression of likelihood of occurrence of an event.A probability isa number which ranges.
Sixth lecture Concepts of Probabilities. Random Experiment Can be repeated (theoretically) an infinite number of times Has a well-defined set of possible.
Chapter 6 Lesson 6.1 Probability 6.1: Chance Experiments and Events.
Lecture 7 Dustin Lueker. 2STA 291 Fall 2009 Lecture 7.
Lecture 6 Dustin Lueker.  Standardized measure of variation ◦ Idea  A standard deviation of 10 may indicate great variability or small variability,
Probability theory is the branch of mathematics concerned with analysis of random phenomena. (Encyclopedia Britannica) An experiment: is any action, process.
Basic probability Sep. 16, Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies.
3.4 Elements of Probability. Probability helps us to figure out the liklihood of something happening. The “something happening” is called and event. The.
Experiments, Outcomes and Events. Experiment Describes a process that generates a set of data – Tossing of a Coin – Launching of a Missile and observing.
1 Probability- Basic Concepts and Approaches Dr. Jerrell T. Stracener, SAE Fellow Leadership in Engineering EMIS 7370/5370 STAT 5340 : PROBABILITY AND.
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Basic Probability. Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies of probability)
Venn Diagrams.
Probability Probability II. Opening Routine # 1.
Project 1 Lecture Notes. Table of Contents Basic Probability Word Processing Mathematics Summation Notation Expected Value Database Functions and Filtering.
AP Statistics From Randomness to Probability Chapter 14.
1 What Is Probability?. 2 To discuss probability, let’s begin by defining some terms. An experiment is a process, such as tossing a coin, that gives definite.
Chapter 6 6.1/6.2 Probability Probability is the branch of mathematics that describes the pattern of chance outcomes.
Subtopic : 10.1 Events and Probability
PROBABILITY AND PROBABILITY RULES
What is Probability? Quantification of uncertainty.
Sample Spaces, Subsets and Basic Probability
Probability Union Intersection Complement
Honors Statistics From Randomness to Probability
Warm-up.
Sets A set is simply any collection of objects
Mrs.Volynskaya Alg.2 Ch.1.6 PROBABILITY
Sample Spaces, Subsets and Basic Probability
Sample Spaces, Subsets and Basic Probability
PROBABILITY Vocabulary: Theory Book
An Introduction to….
Presentation transcript:

Basic Probability Sets, Subsets Sample Space Event, E Probability of an Event, P(E) How Probabilities are assigned Properties of Probabilities

Sets A set is simply any collection of objects A set may be finite or infinite A set with nothing in it is called the empty set (null or void set) and is denoted, { } or ø Two sets are equal if they have exactly the same elements

Subsets If A={1,2,3} is a set then subsets of A include the sets:{ },{1},{2},{3},{1,2}, {1,3},{2,3},{1,2,3} If B is one of the subsets of A then we can say that B  A

Sample Space The set, S, of all distinct possible outcomes of an experiment is called a sample space Suppose we are rolling a die, what is the sample space, S? Suppose we toss a coin twice recording the outcome each time, what is the sample space, S?

Events (E) An event is any collection of outcomes of a probability experiment Suppose we are flipping a coin-what are the events that may occur? Suppose we are rolling a die, what are the events that may occur? What if we flip the coin twice, what are the events that may occur?

Event, con’t Since an event is a collection of outcomes, we can say that E  S What does E mean? What does S stand for? What does E  S mean? An event, E is a subset of a sample space, S.

Exercise Determine the sample space for the experiment: flipping a coin three times Write three events that correspond to this experiment What is P(at least 3 heads)? What is P(at least 3 tails)? What is P(no heads)? What is P(no more than 1 head)?

Another Exercise Suppose as part of a survey on popular music two students are asked whether they like a certain CD, dislike it, or don’t care. What is the sample space? What are the chances that the first student likes the CD? What are the chances that the second student likes the CD?

Another Exercise (cont) How about each of the students either liking or disliking the CD? How about one student liking the CD while the other doesn’t care? What about the second student liking the CD AND one of the students likes the CD while the other doesn’t care?

Probability of an Event Given an event, we would assign it a number, P(E) called the probability of E This number indicates the likelihood that the event will occur. We can find this number by setting up a ratio:

How Probabilities are Assigned Initial Probabilities are usually assigned either: Empirically-when an experiment is repeated a large number of times and you observe the fraction of times E occurs By Authority By Common Agreement

Properties of Probabilities Probabilities must satisfy the following properties: i. For any event, E, 0  P(E)  1 ii. If E is certain to happen then P(E)=1 iii. If E and F are events where E and F cannot happen at the same time, then P(E or F)=P(E)+P(F)

Probability, con’t A set of possible outcomes of an experiment is a sample space, S. P(S)=?

Venn Diagrams The Venn Diagram is made up of two or more overlapping circles or sets. It is often used in mathematics to show relationships between sets.

Venn Diagrams Here is the Venn Diagram associated with the set A.

Complements A complement of A is everything that is in the universal set, U, but not in the set A. The complement is the event that A does not happen. The complement is denoted, A c. Here is the complement of set A.

Unions of sets The union of sets A and B is the set of all items that are either in A or B. We express union, A  B In math, the word “or” also includes members of both A and B.

Intersection of Sets The intersection of sets A and B is the set of all items that are in both A and B. We express intersection, A  B.

Probabilities For any events E and F:

Mutually Exclusive Two events are mutually exclusive if A  B= . If A and B are mutually exclusive, then AB

Mutually Exclusive If no two events E 1,E E n can happen at the same time, then

Review Union of two sets, A  B, is all items that are in set A OR set B Intersection of two sets, A  B, is all items that are in both A AND B A complement of event A, A c, is everything that is in the universal set but not in the set A Two events are mutually exclusive if A  B= 

Review, con’t For any events, E and F: P(E  F)=P(E)+P(F)-P(E  F) We can use this equation to solve for P(E  F), P(E), P(F), or P(E  F) However if E and F are mutually exclusive then: P(E  F)=P(E)+P(F) P(E c )=1-P(E)

De Morgan’s Laws If A and B are any two sets:

Answer the following questions: What is: (A  A c ) = ? (A  A c ) = ? If E and F are mutually exclusive, what is (E  F) = ?