Not a Venn diagram?. Warm up When rolling a die with sides numbered from 1 to 20, if event A is the event that a number divisible by 5 is rolled: i) What.

Slides:



Advertisements
Similar presentations
Probability Simple Events
Advertisements

Chapter 2 Probability. 2.1 Sample Spaces and Events.
How likely something is to happen.
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Probability Sample Space Diagrams.
1 1 PRESENTED BY E. G. GASCON Introduction to Probability Section 7.3, 7.4, 7.5.
1 Chapter 6: Probability— The Study of Randomness 6.1The Idea of Probability 6.2Probability Models 6.3General Probability Rules.
4.2 Probability Models. We call a phenomenon random if individual outcomes are uncertain but there is nonetheless a regular distribution of outcomes in.
Probability The likelihood that an event will occur. A number from 0 to 1 As a percent from 0% to 100%
Section 5.2 The Addition Rule and Complements
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 2 Probability.
Warm up The probability of event A is given by P(A) = n(A) = 8 = 2 n(S) What could event A be? What is the Sample Space, S?
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.
5.1 Basic Probability Ideas
Warm up A ferris wheel holds 12 riders. If there are 20 people waiting to ride it, how many ways can they ride it?
Topics to be covered: Produce all combinations and permutations of sets. Calculate the number of combinations and permutations of sets of m items taken.
College Algebra Sixth Edition James Stewart Lothar Redlin Saleem Watson.
AP Statistics Chapter 6 Notes. Probability Terms Random: Individual outcomes are uncertain, but there is a predictable distribution of outcomes in the.
Warm-Up 1. What is Benford’s Law?
Copyright 2013, 2010, 2007, Pearson, Education, Inc. Section 12.6 OR and AND Problems.
Chapter 1:Independent and Dependent Events
Topic 4A: Independent and Dependent Events Using the Product Rule
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.
Probability Introduction Examples Key words Practice questions Venn diagrams.
1 CHAPTERS 14 AND 15 (Intro Stats – 3 edition) PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY.
1 CHAPTER 7 PROBABILITY, PROBABILITY RULES, AND CONDITIONAL PROBABILITY.
3.3 Finding Probability Using Sets. Set Theory Definitions Simple event –Has one outcome –E.g. rolling a die and getting a 4 or pulling one name out of.
Math I.  Probability is the chance that something will happen.  Probability is most often expressed as a fraction, a decimal, a percent, or can also.
Probability: Terminology  Sample Space  Set of all possible outcomes of a random experiment.  Random Experiment  Any activity resulting in uncertain.
Conditional Probability. Suppose you roll two dice Does the result of one of the dice affect what the result of the second one will be? No These are independent.
Math 30-2 Probability & Odds. Acceptable Standards (50-79%)  The student can express odds for or odds against as a probability determine the probability.
Not a Venn diagram?.
Chapter 4 Review MDM 4U Gary Greer.
Aim: ‘And’ Probabilities & Independent Events Course: Math Lit. Aim: How do we determine the probability of compound events? Do Now: What is the probability.
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.
5-Minute Check on Section 6-2a Click the mouse button or press the Space Bar to display the answers. 1.If you have a choice from 6 shirts, 5 pants, 10.
Section 6.2: Probability Models Ways to show a sample space of outcomes of multiple actions/tasks: (example: flipping a coin and rolling a 6 sided die)
Chapter 10 – Data Analysis and Probability 10.7 – Probability of Compound Events.
Chapter 4 Review MDM 4U Mr. Lieff.
Unit 1 Review ( ) MDM 4U Mr. Lieff. Test Format 20 MC (4 per section) 15 Marks K/U 20 Marks APP (choice 3 of 5) 10 Marks TIPS (choice 2 of 3) 15%
Probability 9.8. Copyright © by Houghton Mifflin Company, Inc. All rights reserved. 2 Definition: Experiment Any activity with an unpredictable results.
2.5 Additive Rules: Theorem 2.10: If A and B are any two events, then: P(A  B)= P(A) + P(B)  P(A  B) Corollary 1: If A and B are mutually exclusive.
Experiments, Outcomes and Events. Experiment Describes a process that generates a set of data – Tossing of a Coin – Launching of a Missile and observing.
Probability. Definitions Probability: The chance of an event occurring. Probability Experiments: A process that leads to well- defined results called.
Project 1 Lecture Notes. Table of Contents Basic Probability Word Processing Mathematics Summation Notation Expected Value Database Functions and Filtering.
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.
Adding Probabilities 12-5
Samples spaces are _______________
Lesson 10.4 Probability of Disjoint and Overlapping Events
Probability Using Venn Diagrams
Probability.
Probability I.
The study of randomness
Good afternoon! August 9, 2017.
Copyright © 2016, 2013, and 2010, Pearson Education, Inc.
Unit 1 Review MDM 4U Chapters 4.1 – 4.5.
Minds on! If you choose an answer to this question at random, what is the probability you will be correct? A) 25% B) 50% C) 100% D) 25%
Probability I.
Probability.
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 I.
Section 6.2 Probability Models
Probability I.
Digital Lesson Probability.
Click the mouse button or press the Space Bar to display the answers.
Mutually Exclusive Events
Warm-Up #10 Wednesday 2/24 Find the probability of randomly picking a 3 from a deck of cards, followed by face card, with replacement. Dependent or independent?
PROBABILITY RANDOM EXPERIMENTS PROBABILITY OF OUTCOMES EVENTS
Sets, Combinatorics, Probability, and Number Theory
Presentation transcript:

Not a Venn diagram?

Warm up When rolling a die with sides numbered from 1 to 20, if event A is the event that a number divisible by 5 is rolled: i) What is the sample space, S? What is n(S)? ii) What is the event space, A? What is n(A)? iii) What is P(A)? i) S = {1, 2, 3, …, 20}, n(S) = 20 ii) A = {5, 10, 15, 20}, n(A) = 4 iii)P(A) = 4/20 = 1/5 or 0.20

4.3 Finding Probability Using Sets Questions? pp #1, 5, 8-10, Learning goals: Construct Venn diagrams and use them to compute probabilities MSIP/Home Learning: p. 228 #1, 2, 4, 7, 8, 10–14, 17

John Venn “Of spare build, he was throughout his life a fine walker and mountain climber, a keen botanist, and an excellent talker and linguist” -- John Archibald Venn (John Venn’s son), writing about his father

A Simple Venn Diagram Venn Diagram: a diagram in which sets are represented by geometrical shapes. A’ A S

Set Notation In mathematics, curly brackets are used to denote a set of items e.g., Define the following sets of numbers  A = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}  B = {2, 4, 6, 8, 10}  C = {1, 2, 3, 4, 5}  D = {10} The items in a set are commonly called elements.

Intersection of Sets Given two sets, A and B, the set of common elements is called the intersection of A and B, is written as A ∩ B (“A intersect B”). S A ∩ B A B

Intersection of Sets (continued) Elements that belong to the set A ∩ B are members of set A and members of set B. So… A ∩ B = {elements in both A AND B} S A ∩ B

Example 1 - Intersection Let A = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}C = {1, 2, 3, 4, 5} B = {2, 4, 6, 8, 10} D = {10} a) What is A ∩ B? {2, 4, 6, 8, 10} or B b) B ∩ C? {2, 4} c) C ∩ D? { } or Ø (the empty set, sounds like the vowel sound in bird or hurt) d) A ∩B ∩D? {10} or D

Union of Sets The set formed by combining the elements of A with those in B is called the union of A and B, and is written A U B. S A U B

Union of Sets (continued) Elements that belong to the set A U B are members of set A or members of set B (or both). So… A U B = {elements in A OR B (or both)} S A U B

Example 2 - Union A = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}B = {2, 4, 6, 8, 10} C = {1, 2, 3, 4, 5}D = {10} a) What is A U B? {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} or A b) B U C? {1, 2, 3, 4, 5, 6, 8, 10} c) C U D? {1, 2, 3, 4, 5, 10} d) B U C U D? {1, 2, 3, 4, 5, 6, 8, 10}

Disjoint Sets A and B are disjoint sets if they have no elements in common  n(A ∩ B) = 0 The intersection of A and B is empty  A ∩ B = Ø What would the Venn diagram look like?

Disjoint Sets (continued) A Venn diagram for two disjoint sets might look like this: S BA

The Additive Principle Remember:  n(A) is the number of elements in set A  P(A) is the probability of event A The Additive Principle for the Union of Two Sets:  n(A U B) = n(A) + n(B) – n(A ∩ B)  P(A U B) = P(A) + P(B) – P(A ∩ B) Alternatively:  n(A ∩ B) = n(A) + n(B) – n(A U B)  P(A ∩ B) = P(A) + P(B) – P(A U B)

Mutually Exclusive Events Mutually exclusive events have no outcomes in common  A and B are mutually exclusive events if and only if (A ∩ B) = Ø  e.g., flipping a head or tail  e.g., drawing a red card or a black card So for mutually exclusive events A and B, n(A U B) = n(A) + n(B)

Example 3 What is the number of cards that are either red cards or face cards? Let R be the set of red cards, F the set of face cards If we have “or” we are looking at union n(R U F) = n(R) + n(F) – n(R ∩ F) = n(red) + n(face) – n(red face) = – 6 = 32 What is the probability of picking a red card or a face card from a standard deck? P(R U F) = 32/52 = 8/13 or 0.62

Example 4 A survey of 100 students How many students study English only? French only? Math only? Course TakenNo. of students English 80 Mathematics 33 French 68 English and Mathematics 30 French and Mathematics 6 English and French 50 All three courses 5 We need to draw a Venn diagram

Example 4: what do we know? n(E ∩ M ∩ F) = 5 M F E 5

Example 4: what else do we know? n(E ∩ M ∩ F) = 5 M F E 5 n(M ∩ E) = 30 Therefore, the number of students in E and M, but not in F is

Example 4 (continued) n(F ∩ E) = 50 Therefore, the number of students who take English and French, but not in Math is 45. M F E n(E) = 80 5

Example 4 – completed Venn Diagram M F E

MSIP / Home Learning Read through Examples 2-3 on pp Complete p. 228 #1, 2, 4, 7, 8, 10–14, 17

Warm up What is the number of cards that are either even numbers (2, 4, 6, 8, 10) or clubs? What is the probability of picking such a card from a standard deck? Use n(E U C) = n(E) + n(C) – n(E ∩ C) = n(even) + n(clubs) – n(even clubs) = – 5 = 28 Probability? P(E U C) = 28/52 = 7/13

4.4 Conditional Probability Learning goal: Calculate probabilities when one event is affected by the occurrence of another Questions? p. 228 #1, 2, 4, 7, 8, 10–14, 17 MSIP/Home Learning: pp. 235 – 238 #1, 2, 4, 6, 7, 9, 10, 19

Conditional Probabilities In some situations, knowing that one event has occurred affects the probability that another event will occur. Examples:  Weather  Sequenced traffic lights  Star athletes’ performance  Dealing cards (no replacement)

Conditional Probability Formula The probability that event B will occur given that event A has occurred is: P(B | A) =P(A ∩ B) P(A)

Example 1a Light 1 and Light 2 are both green 60% of the time. Light 1 is green 80% of the time. What is the probability that Light 2 is green given that Light 1 is green?

Example 1b There is a 20% chance that it will snow both Saturday and Sunday. There is an 80% chance of snow on Saturday. What is the probability that it will snow Sunday given that it snowed Saturday?

Multiplication Law for Conditional Probability The probability of events A and B both occurring, when B is conditional on A is: P(A ∩ B) = P(B|A) x P(A)

Example 2 a) What is the probability of drawing 2 face cards in a row from a deck of 52 playing cards if the first card is not replaced? P(A ∩ B) = P(B | A) x P(A) P(1 st FC ∩ 2 nd FC) = P(2 nd FC | 1 st FC) x P(1 st FC) = 11 x = = 11 or

Example Students surveyed Course TakenNo. of students English 80 Mathematics 33 French 68 English and Mathematics 30 French and Mathematics 6 English and French 50 All three courses 5 Refer to yesterday’s Venn diagram. What is the probability that a student takes Mathematics given that he or she takes English?

Example 3 – Venn Diagram M F E

Another Example (continued) To answer the question, we need to find P(Math | English). We know...  P(Math | English) = P(Math ∩ English) P(English) Therefore…  P(Math | English) = 0.3 = 3 or

MSIP / Home Learning Read Examples 1-3, pp. 231 – 234 pp. 235 – 238 #1, 2, 4, 6, 7, 9, 10, 19