16/4/1435 h Sunday Lecture 2 Sample Space and Events Jan 2009 1.

Slides:



Advertisements
Similar presentations
Beginning Probability
Advertisements

MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Lecture 13 Elements of Probability CSCI – 1900 Mathematics for Computer Science Fall 2014 Bill Pine.
1. Probability of an Outcome 2. Experimental Probability 3. Fundamental Properties of Probabilities 4. Addition Principle 5. Inclusion-Exclusion Principle.
STATISTIK LECTURE: AL MUIZZUDDIN F., SE., ME.. Key Concept In this section we present three different approaches to finding the probability of an event.
Copyright © 2006 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide
0 0 Review Probability Axioms –Non-negativity P(A)≥0 –Additivity P(A U B) =P(A)+ P(B), if A and B are disjoint. –Normalization P(Ω)=1 Independence of two.
Mathematics in Today's World
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 Chapter Independent Events Section
8.7 Probability. Ex 1 Find the sample space for each of the following. One coin is tossed. Two coins are tossed. Three coins are tossed.
1. Experiment, Trial and Outcome 2. Sample Space 3. Event 4. Special Events 5. Events As Sets 6. Mutually Exclusive Events 1.
PROBABILITY  A fair six-sided die is rolled. What is the probability that the result is even?
Aim #10-7: How do we compute probability? Empirical probability applies to situations in which we observe how frequently an event occurs.
Section 1.2 Suppose A 1, A 2,..., A k, are k events. The k events are called mutually exclusive if The k events are called mutually exhaustive if A i 
Bell Work: Factor x – 6x – Answer: (x – 8)(x + 2)
Theoretical Probability Goal: to find the probability of an event using theoretical probability.
Sets, Combinatorics, Probability, and Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS SlidesProbability.
Copyright © 2000 by the McGraw-Hill Companies, Inc. Barnett/Ziegler/Byleen College Algebra: A Graphing Approach Chapter Six Sequences, Series, and Probability.
Bell Quiz.
Simple Mathematical Facts for Lecture 1. Conditional Probabilities Given an event has occurred, the conditional probability that another event occurs.
Copyright © Cengage Learning. All rights reserved. CHAPTER 9 COUNTING AND PROBABILITY.
Counting and Probability. Counting Elements of Sets Theorem. The Inclusion/Exclusion Rule for Two or Three Sets If A, B, and C are finite sets, then N(A.
S.CP.A.1 Probability Basics. Probability - The chance of an event occurring Experiment: Outcome: Sample Space: Event: The process of measuring or observing.
Holt Algebra Basic Principles of Probability Probability is the measure of how likely an event is to occur. Each possible result of a probability.
1.4 Equally Likely Outcomes. The outcomes of a sample space are called equally likely if all of them have the same chance of occurrence. It is very difficult.
The Cosmic Ray Observatory Project High Energy Physics Group The University of Nebraska-Lincoln Counting Random Events A “fair” coin is flipped at the.
Advanced Precalculus Advanced Precalculus Notes 12.3 Probability.
Review Homework pages Example: Counting the number of heads in 10 coin tosses. 2.2/
Probability Prof. Richard Beigel Math C067 September 27, 2006.
Sixth lecture Concepts of Probabilities. Random Experiment Can be repeated (theoretically) an infinite number of times Has a well-defined set of possible.
Introduction to Probability By Dr. Carol A. Marinas.
Probability theory is the branch of mathematics concerned with analysis of random phenomena. (Encyclopedia Britannica) An experiment: is any action, process.
Unit 4 Section 3.1.
Unit 4: Probability Day 2: Basic Probability. Standards and Benchmarks Select and apply counting procedures, such as the multiplication and addition.
Chapter 7: Probability Lesson 1: Basic Principles of Probability Mrs. Parziale.
Probability Lesson 32Power Up GPage 210. Probability.
Chapter 4: Probability. Probability of an Event Definitions An experiment is the process of observing a phenomenon that has variation in its outcomes.
Warm Up: Quick Write Which is more likely, flipping exactly 3 heads in 10 coin flips or flipping exactly 4 heads in 5 coin flips ?
Probability and Simulation The Study of Randomness.
Experiments, Outcomes and Events. Experiment Describes a process that generates a set of data – Tossing of a Coin – Launching of a Missile and observing.
ROLL A PAIR OF DICE AND ADD THE NUMBERS Possible Outcomes: There are 6 x 6 = 36 equally likely.
Chapter 7 Sets & Probability Section 7.3 Introduction to Probability.
When could two experimental probabilities be equal? Question of the day.
Math 1320 Chapter 7: Probability 7.3 Probability and Probability Models.
Random Variables Lecture Lecturer : FATEN AL-HUSSAIN.
2-6 Probability Theoretical & Experimental. Probability – how likely it is that something will happen – Has a range from 0 – 1 – 0 means it definitely.
Counting and Probability. Imagine tossing two coins and observing whether 0, 1, or 2 heads are obtained. Below are the results after 50 tosses Tossing.
Introduction to probability (3) Definition: - The probability of an event A is the sum of the weights of all sample point in A therefore If A1,A2,…..,An.
Adding Probabilities 12-5
Terminologies in Probability
Sec. 4-5: Applying Ratios to Probability
Probability Imagine tossing two coins and observing whether 0, 1, or 2 heads are obtained. It would be natural to guess that each of these events occurs.
Subtopic : 10.1 Events and Probability
Theoretical Probability
Probability Union Intersection Complement
Terminologies in Probability
Terminologies in Probability
Terminologies in Probability
Probability.
COUNTING AND PROBABILITY
Probability Vocabulary:
PROBABILITY Lesson 10.3A.
Chapter 4 Section 1 Probability Theory.
Terminologies in Probability
7.2 Union, intersection, complement of an event, odds
Probability of two events
e is the possible out comes for a model
Terminologies in Probability
Terminologies in Probability
Presentation transcript:

16/4/1435 h Sunday Lecture 2 Sample Space and Events Jan

Number of Elements in a Sample Space Number of elements in = number of elements in n a sample space a sample space in one experiment Where: n is a number of time the experiment is repeated Examples: 1. Toss a coin A. Once = 2 1 =2 elements B. Twice = 2 2 =4 elements Jan

. C. Three times = 2 3 = 8 elements 2. Roll a fair die: A. Once: = 6 1 = 6 elements B. Twice: = 6 2 = 36 elements Jan

1.Sample Space and Events For Simple Events 1.Roll a die Once A six-sided die has this sample space Number of elements in the sample space = = 6 1 = 6 elements  Sample space: S = {1, 2, 3, 4, 5, 6}  Simple events (or outcomes): E1= {1}, E2 = {2}, E3 = {3} E4 = {4} E5 = {5} E6 = {6} 4

2.Toss a coin once Q: Show the sample space  Sample space: Number of elements in the sample space = = 2 1 = 2 Where: H = Head T = Tail  Simple events (or outcomes): E1( Head) = {H} E2(Tail} = {T} Jan

0 2. Sample Space and Events For Compound Events 1. Roll a die Q: Observe these events A: odd numbers A = {1, 3, 5} B: observe an even number B= {2, 4, 6} C: observe a number greater than or equal to 4 C= {4, 5, 6} D: observe a number less than or equal to 4 D = {4, 3, 2,1} Jan

. 2. The roll of a Two dice Q: Show the sample space when two unbiased dice were rolled or (if one die is rolled twice) Number of elements in the sample space = = 6 2 = 36 elements

. Jan

. Examples that shows compound events of rolling two dice: Q: show the event of Sum of 6 A: = { (1,5),(5,1),(2,4),(4,2),(3,3)} Q: show the event that shows similar faces B= {(1,1),(2,2),(3,3),(4,4),(5,5),(6,6,)} Jan

3.Toss a coin twice Q:Show the sample space? The number of elements in the sample space = 2 2 = 4 elements Show these events: A: Observe the number of heads A = { 0, 1, 2, } B : Having exactly two head B={(H,H)} C: Having at least one head C = {(H,H),(H,T),(T,H)} Jan

. D: Observe the number of tails D = { 0, 1, 2, } E: Having exactly two tail E={(T,T)} F: Having at least one tail F = {(T,T),(H,T),(T,H)} 4. Toss a coin three times Q: Show the sample space The number of elements in the sample space = 2 3 = 8 elements S={(H,H,H),(H,H,T),(H,T,H),(T,H,H),(H,T,T),(T,H,T),(T,T,H),(T,T,T)} Q: Observe the number of heads S = { 0, 1, 2,3 } Jan

. Q: Observe these events A: number of Tails A = { 0, 1, 2,3 } B: Having at least one head B={(T,H,T), (H,T,T),(T,T,H), (H,T,H),(T,H,H), (H,H,T),(H,H,H),} C: Show the sample space that represents the working state of a machine C = { working, fail } D: Show the sample space that represents the n umber of calls arriving at a telephone exchange during a specific time interval D = { 0, 1, …} Jan