Middle Tennessee State University ©2013, MTStatPAL.

Slides:



Advertisements
Similar presentations
Probability Simple Events
Advertisements

Probability Denoted by P(Event) This method for calculating probabilities is only appropriate when the outcomes of the sample space are equally likely.
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.
Randomness and Probability
Probability Chapter 11 1.
Aim #10-7: How do we compute probability? Empirical probability applies to situations in which we observe how frequently an event occurs.
1 Independence Supplementary Notes Prepared by Raymond Wong Presented by Raymond Wong.
Probabilities of common Games How do I avoid bad bets?
Warm-up The mean grade on a standardized test is 88 with a standard deviation of 3.4. If the test scores are normally distributed, what is the probability.
Academy Algebra II/Trig 14.3: Probability HW: worksheet Test: Thursday, 11/14.
Copyright © 2015, 2011, 2008 Pearson Education, Inc. Chapter 7, Unit A, Slide 1 Probability: Living With The Odds 7.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 6: Probability: What are the Chances? Section 6.1 Randomness and Probability.
Chapter 5 Probability ( ).
5.1 Basic Probability Ideas
Probability Denoted by P(Event) This method for calculating probabilities is only appropriate when the outcomes of the sample space are equally likely.
CHAPTER 4 PROBABILITY.
Chapter 6 Random Variables. Make a Sample Space for Tossing a Fair Coin 3 times.
1 Introduction to Discrete Probability Rosen, Section 6.1 Based on slides by Aaron Bloomfield and …
“Baseball is 90% mental. The other half is physical.” Yogi Berra.
Bell Quiz.
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.
Probability Denoted by P(Event) This method for calculating probabilities is only appropriate when the outcomes of the sample space are equally likely.
Chapters 14/15 AP Statistics Mrs. Wolfe
POSC 202A: Lecture 5 Today: Expected Value. Expected Value Expected Value- Is the mean outcome of a probability distribution. It is our long run expectation.
III. Probability B. Discrete Probability Distributions
1 M14 Expected Value, Discrete  Department of ISM, University of Alabama, ’95,2002 Lesson Objectives  Understand the meaning of “expected value.” (Know.
Outline Random processes Random variables Probability histograms
Probability Post-Class Activity. Review of class Empirical probability – based on observed data. Theoretical probability – based on a model of the experiment.
Seminar 7 MM150 Bashkim Zendeli. Chapter 7 PROBABILITY.
Basic Probability Section 7.1. Definitions Sample Space: The set of all possible outcomes in a given experiment or situation Often denoted by S Event:
Chapter 9 Review. 1. Give the probability of each outcome.
Probability 2 Compound Probability.  Now lets consider the following:  2 dice are rolled and the numbers are added together.  What are the numbers.
THE NATURE OF PROBABILITY Copyright © Cengage Learning. All rights reserved. 13.
Lesson 3-6. Independent Event – 1st outcome results of probability DOES NOT affect 2nd outcome results Dependent Event – 1st outcome results of probability.
Expected Value.
MM207 Statistics Welcome to the Unit 7 Seminar With Ms. Hannahs.
PROBABILITY (Theoretical) Predicting Outcomes. What is probability? Probability refers to the chance that an event will happen. Probability is presented.
Probability Basics Section Starter Roll two dice and record the sum shown. Repeat until you have done 20 rolls. Write a list of all the possible.
Dr. Fowler AFM Unit 7-8 Probability. Copyright © 2012 Pearson Education, Inc. Publishing as Prentice Hall.
Chapter 14: From Randomness to Probability Sami Sahnoune Amin Henini.
Introduction to Probability (Dr. Monticino). Assignment Sheet  Read Chapters 13 and 14  Assignment #8 (Due Wednesday March 23 rd )  Chapter 13  Exercise.
Slide Copyright © 2009 Pearson Education, Inc. Chapter 7 Probability.
Welcome to our seventh seminar! We’ll begin shortly.
Examples 1.At City High School, 30% of students have part- time jobs and 25% of students are on the honor roll. What is the probability that a student.
Warm up 1)What is the theoretical probability of rolling the sum of 3 on two dice? 2)What is the experimental probability of each color if you rolled a.
Unit 7: Probability. 7.1: Terminology I’m going to roll a six-sided die. Rolling a die is called an “experiment” The number I roll is called an “outcome”
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 5 Probability: What Are the Chances? 5.2.
Section 6.2: Definition of Probability. Probability of an event E denoted P(E) is the ratio of the number of outcomes favorable to E to the total number.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Probability 5.
Gambling and probability 1. Odds and football.  Predict the Premier League results for this weekend.  Can you estimate the probability of a win/draw/loss.
The Law of Averages. What does the law of average say? We know that, from the definition of probability, in the long run the frequency of some event will.
DO NOW 4/27/2016 Find the theoretical probability of each outcome. 1. rolling a 6 on a number cube. 2. rolling an odd number on a number cube. 3. flipping.
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.
Introductory Statistics. Probability Heads or Tails Parents Getting a Girl Blood Type Getting Brown Eyes Rolling a Seven in a game of monopoly Probability.
Probability II.
What Is Probability?.
Probability Rules.
Probability Theoretical Probability
Chapter 12 From Randomness to Probability.
Section 4.2 Probability Rules
Probability II.
A casino claims that its roulette wheel is truly random
= Basic Probability Notes Basics of Probability Probability
(Single and combined Events)
1.9 Probability.
6.2 Basics of Probability LEARNING GOAL
A casino claims that its roulette wheel is truly random
Data Analysis and Statistical Software I ( ) Quarter: Autumn 02/03
Probability Mutually exclusive and exhaustive events
Presentation transcript:

Middle Tennessee State University ©2013, MTStatPAL

Empirical probability – based on observed data. Theoretical probability – based on a model of the experiment. Law of large numbers – As the number of repetitions gets large, the empirical probability gets close to the theoretical probability.

The choice of scenario does not affect the underlying probability model.

Probability Rules: Probabilities must be ≥ 0 and ≤ 1. The total probability should equal 1.

Roulette Playing Cards Drop candy on a plate with more than two divisions. Medical outcomes Business decisions Results of scientific measurements

In Roulette, a person wins if the ball falls on the number they have chosen. There are 38 numbers total: 1-36, 0, and 00. Half of 1-36 are red, half are black. 0 and 00 are green.

Assuming the wheel is fair, what is the probability of getting any one specific number? Remembering that there are 38 numbers total, the probability of getting any one of them is 1/38.

What is the probability of not getting a 15? There are 37 numbers that are not 15, and 38 total, so the probability of not getting 15 is 37/38. Notice that P(not 15) = 1 – P(15)

P(E C ) = 1 - P(E) Probability Rules: Probabilities must be ≥ 0 and ≤ 1. The total probability should equal 1.

Suppose you bet on 15. You continue to play, always betting on 15, 100 times. What do you expect to happen?

What is the probability of getting a red number? There are 18 red numbers, and 38 numbers total, so the probability of getting a red number is 18/38.

What is the probability of getting a black number? Is it the same as the probability of not getting a red number?

Suppose you bet on red. You continue to play, always betting on red, 100 times. What do you expect to happen?

One of the bets in Roulette is called a “square bet.” By placing your chip on the square formed by four numbers, you bet on all four of them. One such square contains the numbers 2, 3, 5, and 6.

Suppose you bet on both this square bet (above) and on the red numbers. What is the probability that at least one of your bets pays off?

P(square or red) = P(square) + P(red)

1, 7, 9, 12, 14, 16, 18, 19, 21, 23, 25, 27, 30, 32, 34, 36 3, 5 4, 8, 10, 11, 13, 15, 17, 20, 22, 24, 26, 28, 29, 31, 33, 35 2, 6

P(square or red) = P(square) + P(red) – P(square and red) = 4/ /38 – 2/38 = 20/38

P(E or F) = P(E) + P(F) – P(E and F) If no overlap, this becomes the addition rule for disjoint events: P(E or F) = P(E) + P(F)

Probability Rules: Probabilities must be ≥ 0 and ≤ 1. The total probability should equal 1. Complement Rule: P(E C ) = 1 - P(E) Addition Rules: P(E or F) = P(E) + P(F) – P(E and F) P(E or F) = P(E) + P(F) (If events are disjoint.)