Section 2 Complements and Unions of Events Objectives: Understand the relationship between the probability of an event and the probability of its complement.

Slides:



Advertisements
Similar presentations
Natalia Sivackova. Events that cannot happen together (e.g. cant a card that is both red and black in a card deck) P(A B) = P(A) + P(B)
Advertisements

Aim: What are ‘Or’ Probabilities?
Bellwork You roll a fair die one time, find each probability below.
Math 7 Unit 6 Test Review.
Probability I Introduction to Probability
Probability and Conditional Probability. Probability Four balls What is the probability of choosing the ball in the red box? Since there are four balls.
Chapter 15 Probability Rules!.
Consumer Math Mastery test a
Sl No Top-up Amount No Of Affiliate Ads Payment Per Day By Affiliate Ad Total Affiliate Ad Income 1.5,000/- Daily 2 ad for 100 days 100/- Affiliate.
Beginning Probability
What are the odds?. To find the probability that a man has both a beard and a mustache would you multiply the probability of a man having a beard by the.
Discrete Distributions
Two-Way Tables and Venn Diagrams
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Business and Economics 6th Edition
{ 11.3 Dependent Events Apply probability concepts such as intersections, unions and complements of events, and conditional probability and independence,
Basic Probability: Outcomes and Events 4/6/121. Counting in Probability What is the probability of getting exactly two jacks in a poker hand? lec 13W.2.
Unions and Intersections  When you consider all the outcomes for either of two events, A and B, you form the union of A and B.  When you consider only.
Probability COMPOUND EVENTS. If two sets or events have no elements in common, they are called disjoint or mutually exclusive. Examples of mutually exclusive.
Probability Ch 14 IB standard Level.
1.6 – Solving Compound and Absolute Value Inequalities
Straight Line Equation.
Chapter 14 worksheet.
3 - 1 Copyright McGraw-Hill/Irwin, 2005 Markets Demand Defined Demand Graphed Changes in Demand Supply Defined Supply Graphed Changes in Supply Equilibrium.
Independence and the Multiplication Rule
Chapter 3 Section 3.3 Basic Rules of Probability.
Chapter 4 Lecture 2 Section: 4.3. Addition Rule We will now consider compound events. Previously we considered simple events. Compound Event: is any event.
EXAMPLE 4 Find a conditional probability Weather The table shows the numbers of tropical cyclones that formed during the hurricane seasons from 1988 to.
EXAMPLE 1 Find probability of disjoint events
EXAMPLE 4 Find a conditional probability Weather The table shows the numbers of tropical cyclones that formed during the hurricane seasons from 1988 to.
EXAMPLE 3 Find odds A card is drawn from a standard deck of 52 cards. Find (a) the odds in favor of drawing a 10 and (b) the odds.
Sets, Combinatorics, Probability, and Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS SlidesProbability.
Sets, Combinatorics, Probability, and Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS SlidesProbability.
Chapter 5: Probability Distribution What is Probability Distribution? It is a table of possible outcomes of an experiment and the probability of each outcome.
Copyright 2013, 2010, 2007, Pearson, Education, Inc. Section 11.3 Compound Interest.
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 1 Section 13-6 Regression and Correlation.
Section 1.1, Slide 1 Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 13.3, Slide 1 13 Probability What Are the Chances?
Section 1.1, Slide 1 Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 13.3, Slide 1 13 Probability What Are the Chances?
Topic 4A: Independent and Dependent Events Using the Product Rule
Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
Section 1.1, Slide 1 Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 13.2, Slide 1 13 Probability What Are the Chances?
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin A Survey of Probability Concepts Chapter 5.
SECTION 11-3 Conditional Probability; Events Involving “And” Slide
12.4 Probability of Compound Events. Vocabulary Compound Event: the union or intersection of two events. Mutually Exclusive Events: events A and B are.
Copyright 2013, 2010, 2007, Pearson, Education, Inc. Section 12.7 Conditional Probability.
Probability Rules In the following sections, we will transition from looking at the probability of one event to the probability of multiple events (compound.
Copyright © 2015, 2008, 2011 Pearson Education, Inc. Section 2.4, Slide 1 Chapter 2 Modeling with Linear Functions.
EXAMPLE 1 Find probability of disjoint events A card is randomly selected from a standard deck of 52 cards. What is the probability that it is a 10 or.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 5 Section 2 – Slide 1 of 21 Chapter 5 Section 2 The Addition Rule and Complements.
SECTION 11-2 Events Involving “Not” and “Or” Slide
Chapter 10 – Data Analysis and Probability 10.7 – Probability of Compound Events.
Copyright © 2009 Pearson Education, Inc. Chapter 12 Section 2 - Slide 1 P-2 Probability Theoretical Probability.
THE MATHEMATICAL STUDY OF RANDOMNESS. SAMPLE SPACE the collection of all possible outcomes of a chance experiment  Roll a dieS={1,2,3,4,5,6}
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Learning Objectives for Section 8.4 Bayes’ Formula The student will be able to solve problems involving.
Probability Models Vocabulary Terms Mutually Exclusive/Disjoint General Addition Rule.
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.
Section 13.2 Complements and Union of Events. Objective 1.Finding the probability that an event will not occur. 2.Find the probability of one event or.
What Is Probability?.
Chapter 10 Counting Methods.
Bellwork Perform Synthetic Division and explain what is the solution of the synthetic division represent?
13.2 Complements and Unions of Events
12.4 Probability of Compound Events
Probability I.
Experiments, Sample Spaces, and Events
Section 12.2 Theoretical Probability
Section 12.2 Theoretical Probability
Chapter 4 Lecture 2 Section: 4.3.
Question 24.
Section 12.2 Theoretical Probability
Sets, Combinatorics, Probability, and Number Theory
Presentation transcript:

Section 2 Complements and Unions of Events Objectives: Understand the relationship between the probability of an event and the probability of its complement. Calculate the probability of the union of two events. Use complement and union formulas to compute the probability of an event.

Complements of Events

Complements of Events (2) Example: The graph shows the party affiliation of a group of voters. If we randomly select a person from this group, what is the probability that the person has a party affiliation?

Complements of Events (3) Solution: Let A be the event that the person we select has some party affiliation. It is simpler to calculate the probability of A‘ since 23.7% have no party affiliation. P(A) = 1 – P(A') = 1 – =

Unions of Events

Unions of Events (2) Example: If we select a single card from a standard 52-card deck, what is the probability that we draw either a heart or a face card? Solution: Let H be the event “draw a heart” and F be the event “draw a face card.” We are looking for P(H U F).

Unions of Events (3) There are 13 hearts, 12 face cards, and 3 cards that are both hearts and face cards.

Unions of Events (3) Example: A survey found that 35% of a group of people were concerned with improving their cardiovascular fitness and 55% wanted to lose weight. Also, 70% are concerned with either improving their cardiovascular fitness or losing weight. If a person is randomly selected from the group, what is the probability that the person is concerned with both improving cardiovascular fitness and losing weight? Solution: Let C be the event “the person wants to improve cardiovascular fitness” and W be the event “the person wishes to lose weight.” We need to find P(C ∩ W). We have P(C) = 0.35, P(W) = 0.55, and P(C U W) = P(C ∩ W) = __________________

Combining Complement and Union Formulas Example: A survey of consumers shows the amount of time they spend shopping on the Internet per month compared to their annual income (see next slide). If we select a consumer randomly, what is the probability that the consumer neither shops on the Internet 10 or more hours per month nor has an annual income above $60,000? Let T be the event “the consumer selected spends 10 or more hours per month shopping on the Internet.” Let A be the event “the consumer selected has an annual income above $60,000.”

Combining Complement and Union Formulas (2) From the table we get n(T) = = 480 and n(A) = = 496. With n(S) = 1,600, we may compute the probabilities below.