Probability Objectives When you have competed it you should * know what a ‘sample space’ is * know the difference between an ‘outcome’ and an ‘event’.

Slides:



Advertisements
Similar presentations
Chapter 3 Probability.
Advertisements

Basic Concepts of Probability
Larson/Farber 4th ed 1 Basic Concepts of Probability.
Randomness and Probability
© 2011 Pearson Education, Inc
1 Counting. 2 Situations where counting techniques are used  You toss a pair of dice in a casino game. You win if the numbers showing face up have a.
Section 7A: Fundamentals of Probability Section Objectives Define outcomes and event Construct a probability distribution Define subjective and empirical.
From Randomness to Probability
Solve for x. 28 = 4(2x + 1) = 8x = 8x + 8 – 8 – 8 20 = 8x = x Distribute Combine Subtract Divide.
Probability Sample Space Diagrams.
Copyright © Cengage Learning. All rights reserved. 8.6 Probability.
Chapter 3 Probability.
Nuffield Free-Standing Mathematics Activity
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.
Bell Work: Collect like terms: x + y – 1 – x + y + 1.
The chance or likelihood of something happening
Probability Chapter 3. § 3.1 Basic Concepts of Probability.
14.7 Probability and Odds CORD Math Mrs. Spitz Spring 2007.
Sample space The set of all possible outcomes of a chance experiment –Roll a dieS={1,2,3,4,5,6} –Pick a cardS={A-K for ♠, ♥, ♣ & ♦} We want to know the.
Chapter 3 Section 3.2 Basic Terms of Probability.
CONFIDENTIAL 1 Algebra1 Experimental Probability.
Principles of Statistics Chapter 2 Elements of Probability.
PROBABILITY. Counting methods can be used to find the number of possible ways to choose objects with and without regard to order. The Fundamental Counting.
Probability Section 7.1.
Basic Concepts of Probability Coach Bridges NOTES.
C4, L1, S1 Chapter 3 Probability. C4, L1, S2 I am offered two lotto cards: –Card 1: has numbers –Card 2: has numbers Which card should I take so that.
Copyright © Cengage Learning. All rights reserved. 8.6 Probability.
Chapter 3 Probability Larson/Farber 4th ed. Chapter Outline 3.1 Basic Concepts of Probability 3.2 Conditional Probability and the Multiplication Rule.
Chapter Probability 1 of 88 3 © 2012 Pearson Education, Inc. All rights reserved.
1 RES 341 RESEARCH AND EVALUATION WORKSHOP 4 By Dr. Serhat Eren University OF PHOENIX Spring 2002.
Review Homework pages Example: Counting the number of heads in 10 coin tosses. 2.2/
Introduction  Probability Theory was first used to solve problems in gambling  Blaise Pascal ( ) - laid the foundation for the Theory of Probability.
Sixth lecture Concepts of Probabilities. Random Experiment Can be repeated (theoretically) an infinite number of times Has a well-defined set of possible.
Basic Concepts of Probability
Measuring chance Probabilities FETP India. Competency to be gained from this lecture Apply probabilities to field epidemiology.
BIA 2610 – Statistical Methods
Probability. What is probability? Probability discusses the likelihood or chance of something happening. For instance, -- the probability of it raining.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Probability 3.
11.7 Continued Probability. Independent Events ► Two events are independent if the occurrence of one has no effect on the occurrence of the other ► Probability.
Probability Chapter 3. § 3.1 Basic Concepts of Probability.
Probability VOCAB!. What is probability? The probability of an event is a measure of the likelihood that the event will occur. When all outcomes are equally.
PROBABILITY bability/basicprobability/preview.we ml.
Probability. Today we will look at… 1.Quick Recap from last week 2.Terminology relating to events and outcomes 3.Use of sample spaces when dealing with.
Chapter 10 PROBABILITY. Probability Terminology  Experiment: take a measurement Like flipping a coin  Outcome: one possible result of an experiment.
Ch 11.7 Probability. Definitions Experiment – any happening for which the result is uncertain Experiment – any happening for which the result is uncertain.
Section 4.1 What is Probability ? Larson/Farber 4th ed 1.
Definitions Addition Rule Multiplication Rule Tables
PROBABILITY Probability Concepts
Chapter 3: Probability Topics
Sequences, Series, and Probability
Chapter 3 Probability Larson/Farber 4th ed.
Chapter 3 Probability.
Basic Concepts of Probability
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%
4.5 – Finding Probability Using Tree Diagrams and Outcome Tables
From Randomness to Probability
Probability Chapter 8.
Unit 1: Probability and Statistics
Elementary Statistics: Picturing The World
Probability Probability underlies statistical inference - the drawing of conclusions from a sample of data. If samples are drawn at random, their characteristics.
Probability Trees By Anthony Stones.
Chapter 3 Probability.
Chapter 3 Probability.
Chapter 3 Probability Larson/Farber 4th ed.
Section 1.1: Equally Likely Outcomes
Chapter 4 Section 1 Probability Theory.
Digital Lesson Probability.
M248: Analyzing data Block A UNIT A3 Modeling Variation.
A random experiment gives rise to possible outcomes, but any particular outcome is uncertain – “random”. For example, tossing a coin… we know H or T will.
Presentation transcript:

Probability Objectives When you have competed it you should * know what a ‘sample space’ is * know the difference between an ‘outcome’ and an ‘event’. * know about different ways of estimating probabilities. Key terms: Sample space, Event, Complement of event, Trial/Experiment, Outcome.

Probability is a measure of the likelihood that something happening. Estimating Probability There are three different ways of estimating probabilities. Method A: Theoretical estimation: Use symmetry i.e. counts equally likely outcomes. e.g. The probability of head ( P(H) ) when a coin is tossed. Probability

Estimating Probability Method B: Experimental estimation: Collect data from an experiment or survey. e.g. What is the estimated probability of a drawing pin landing point upwards when dropped onto a hard surface. Method C: Make a subjective estimate When we cannot estimate a probability using experimental methods or equally likely outcomes, we may need to use a subjective method. e.g. What is the estimated probability of my plane crashing as it lands at a certain airport?

Sample space The list of all the possible outcomes is called the sample space s of the experiment It is important in probability to distinguish experiments from the outcomes which they may generate. Experiment Possible outcomes Tossing a coin (H, T) Throwing a die (1, 2, 3, 4, 5, 6) Guessing the answer to a four multiple choice question (A, B, C, D)

The complement of an event The event ‘not A’ is called the complement of the event. The symbol A 1 is used to denote the complement of A. P(A) + P(A 1 ) = 1 An Event is a defined situation. e.g. Scoring a six on the throw of an ordinary six- sided die. An event A s A A1A1

Probability of an event A coin is tossed twice and we are interested in the event (A) that give the same result. Example Solution Sample space =HH, HT, TH, TT Event A =(HH, TT) P(A) = 2 / 4 = ½ Note: 0  P(A)  1

Example 1 The possibility space consists of the integers from 1 to 25 inclusive. A is the event ‘the number is a multiple of 5’. is the event ‘the number is a multiple of 3’. An integer is picked at random. Find (a) P(A), (b) P(B 1 )

Solution Possibility space n(s) = 25 (a) Number of outcomes in event A n(A) = 5 (5, 10, 15, 20 and 25) = 5 / 25 = 1 / 5 (b) P(B 1 ) = 1 – P(B) =1 - 8 / 25 =17 / 25

Example 2 A cubicle die, number 1 to 6, is weighted so that a six is three times as likely to occur as any other number. Find the probability of (a) a six accurring, (b) an even number occurring.

Solution Possibility space n(s) = {1, 2, 3, 4, 5, 6, 6, 6, } = n(s) = 8 (a) P( a six) = 3/83/8 (b) P( an even number) = 5/85/8

A, 24 0 B, 99 0 C D, E, 42 0 Example: A car manufacturer carried out a survey in which people were asked which factor from the following list influenced them when buying a car: A: Colour B: Service cost C: Safety D: Fuel economy E: Extras The names of those who took part were then placed in a prize draw. Find the probability that someone who said safety will win the prize.

A, 24 0 B, 99 0 C D, E, 42 0 Solution: C = 360 – ( ) = 75 P(C) = 75 / 360 = 25 / 120 = 5 / 24