Counting Methods and Probability Theory

Slides:



Advertisements
Similar presentations
Beginning Probability
Advertisements

Probability Simple Events
Basic Terms of Probability Section 3.2. Definitions Experiment: A process by which an observation or outcome is obtained. Sample Space: The set S of all.
Describing Probability
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Thinking Mathematically
Thinking Mathematically Fundamentals of Probability.
Aim #10-7: How do we compute probability? Empirical probability applies to situations in which we observe how frequently an event occurs.
11.1 – Probability – Basic Concepts Probability The study of the occurrence of random events or phenomena. It does not deal with guarantees, but with the.
1 Probability Parts of life are uncertain. Using notions of probability provide a way to deal with the uncertainty.
1 Definitions Experiment – a process by which an observation ( or measurement ) is observed Sample Space (S)- The set of all possible outcomes (or results)
AP STATISTICS.   Theoretical: true mathematical probability  Empirical: the relative frequency with which an event occurs in a given experiment  Subjective:
Section 5.1 What is Probability? 5.1 / 1. Probability Probability is a numerical measurement of likelihood of an event. The probability of any event is.
The Basics of Probability Theory Section 13.1 NCSCOS 2.02.
The Basics of Probability Theory MATH 102 Contemporary Math S. Rook.
Basic Concepts of Probability Coach Bridges NOTES.
Chapter 3 Probability Larson/Farber 4th ed. Chapter Outline 3.1 Basic Concepts of Probability 3.2 Conditional Probability and the Multiplication Rule.
Review Homework pages Example: Counting the number of heads in 10 coin tosses. 2.2/
Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
13.3 Conditional Probability and Intersections of Events Understand how to compute conditional probability. Calculate the probability of the intersection.
Conditional Probability and Intersection of Events Section 13.3.
Basic Concepts of Probability
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
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
1 Chapter 4, Part 1 Basic ideas of Probability Relative Frequency, Classical Probability Compound Events, The Addition Rule Disjoint Events.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 11 Counting Methods and Probability Theory.
Copyright © 2009 Pearson Education, Inc. Chapter 12 Section 2 - Slide 1 P-2 Probability Theoretical Probability.
Probability and Simulation The Study of Randomness.
Chapter 7 Sets & Probability Section 7.3 Introduction to Probability.
Chapter 11 Sequences, Induction, and Probability Copyright © 2014, 2010, 2007 Pearson Education, Inc Probability.
Probability IIntroduction to Probability ASatisfactory outcomes vs. total outcomes BBasic Properties CTerminology IICombinatory Probability AThe Addition.
Calculate theoretical probabilities and find the complement of an event.
Terminologies in Probability
Mathematics Department
9.8 Probability Basic Concepts
Chapter 4 Probability Concepts
11.1 – Probability – Basic Concepts
Sequences, Series, and Probability
Probability of Independent Events
11.4 Fundamentals of Probability
= Basic Probability Notes Basics of Probability Probability
5.1 Probability of Simple Events
AND.
PROBABILITY The probability of an event is a value that describes the chance or likelihood that the event will happen or that the event will end with.
Introduction Remember that probability is a number from 0 to 1 inclusive or a percent from 0% to 100% inclusive that indicates how likely an event is to.
PROBABILITY AND STATISTICS
Chapter 3 Probability.
Chapter 4 Basic Probability.
Terminologies in Probability
Terminologies in Probability
Terminologies in Probability
Chapter 4 Section 1 Probability Theory.
Copyright © 2014, 2010, 2007 Pearson Education, Inc.
Chapter 11: Further Topics in Algebra
Section 11.7 Probability.
Counting Methods and Probability Theory
Counting Methods and Probability Theory
Mrs.Volynskaya Alg.2 Ch.1.6 PROBABILITY
Section 12.2 Theoretical Probability
Terminologies in Probability
Section 12.2 Theoretical Probability
6.1 Sample space, events, probability
Adapted from Walch Education
Video .
Terminologies in Probability
Terminologies in Probability
Section 12.2 Theoretical Probability
Dr. Fowler  AFM  Unit 7-8 Probability.
Theoretical Probability
Presentation transcript:

Counting Methods and Probability Theory CHAPTER 11 Counting Methods and Probability Theory

Fundamentals of Probability 11.4 Fundamentals of Probability

Objectives Compute theoretical probability. Compute empirical probability.

Probability Probabilities are assigned values from 0 to 1. The closer the probability of a given event is to 1, the more likely it is that the event will occur. The closer the probability of a given event is to 0, the less likely that the event will occur.

Theoretical Probability Experiment is any occurrence for which the outcome is uncertain. Sample space is the set of all possible outcomes of an experiment , denoted by S. Event, denoted by E is any subset of a sample space. Sum of the theoretical probabilities of all possible outcomes is 1.

Computing Theoretical Probability If an event E has n(E) equally likely outcomes and its sample space S has n(S) equally-likely outcomes, the theoretical probability of event E, denoted by P(E), is: P(E) = number of outcomes in event E = n(E) total number of possible outcomes n(S)

Example: Computing Theoretical Probability A die is rolled once. Find the probability of rolling 3 b. an even number Solution: The sample space is S = {1,2,3,4,5,6} a. There is only one way to roll a 3 so n(E) = 1. P(3) = number of outcomes that result in 3 = n(E) = 1 total number of possible outcomes n(S) 6 b. Rolling an even number describes the event E = {2,4,6}. This event can occur in 3 ways: n(E) = 3. P(even number) = number of outcomes that result in even number = n(E) = 3 =1 total number of possible outcomes n(S) 6 2

Example: Probability and a Deck of 52 Cards You are dealt one card from a standard 52-card deck. Find the probability of being dealt a a king b. a heart Solution:

Empirical Probability Applies to situations in which we observe how frequently an event occurs. Computing Empirical Probability The empirical probability of event E is: P(E) = observed number of times E occurs = n(E) total number of observed occurrences n(S)

Example: Computing Empirical Probability If one person is randomly selected from the population described above, find the probability that the person is female. Solution: The probability of selecting a female is the observed number of females, 124 (million), divided by the total number of U.S. adults, 242 (million).