Expected Value MM1D2 Students will use the basic laws of probabilities. d. Use expected value to predict outcomes.

Slides:



Advertisements
Similar presentations
: Estimating Probabilities by Collecting Data. Carnival At the school carnival, there is a game in which students spin a large spinner. The spinner has.
Advertisements

Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
EXAMPLE 1 Construct a probability distribution
EXAMPLE 1 Construct a probability distribution Let X be a random variable that represents the sum when two six-sided dice are rolled. Make a table and.
Probability And Expected Value ————————————
1 Probability. 2 Probability has three related “meanings.” 1. Probability is a mathematical construct. Probability.
 The Law of Large Numbers – Read the preface to Chapter 7 on page 388 and be prepared to summarize the Law of Large Numbers.
Discrete Probability Distributions
Discrete Probability Distributions
Unit 6 – Data Analysis and Probability
1 Overview This chapter will deal with the construction of probability distributions by combining the methods of Chapter 2 with the those of Chapter 4.
The possible outcomes are 2 + 2, 2 + 3, 2 + 4, 3 + 2, 3 + 3, 3 + 4, 4 + 2, 4 + 3, The probability of an even sum is ____. The probability of an.
Chapter 3 Section 3.5 Expected Value. When the result of an experiment is one of several numbers, (sometimes called a random variable) we can calculate.
Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.
Estimating Probabilities by Collecting Data
Lesson 9-1 Pages Simple Events Lesson Check Ch 8.
Unit 4: Probability Distributions and Predictions 4.1 Probability Distributions and Expected Value.
A study of education followed a large group of fourth-grade children to see how many years of school they eventually completed. Let x be the highest year.
Chapter 5.1 Probability Distributions.  A variable is defined as a characteristic or attribute that can assume different values.  Recall that a variable.
1 M14 Expected Value, Discrete  Department of ISM, University of Alabama, ’95,2002 Lesson Objectives  Understand the meaning of “expected value.” (Know.
1 Chapter 4. Section 4-1 and 4-2. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
Seminar 7 MM150 Bashkim Zendeli. Chapter 7 PROBABILITY.
Mean and Standard Deviation of Discrete Random Variables.
1.3 Simulations and Experimental Probability (Textbook Section 4.1)
Probability Distributions. We need to develop probabilities of all possible distributions instead of just a particular/individual outcome Many probability.
I expect to see… 1.The variables defined. 2.The equation written for the problem. 3.Work shown in solving the equation. 4.A statement written answering.
MM1D2d: Use expected value to predict outcomes
Not So Great Expectations! Which game do you think has the highest return per dollar?
Transparency 1 Click the mouse button or press the Space Bar to display the answers.
The Binomial Distribution
Chapter 2: Understanding Probability 2.6 Theoretical & Experimental Probability.
Chapter 8: Probability: The Mathematics of Chance Lesson Plan Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Continuous.
4.3 More Discrete Probability Distributions NOTES Coach Bridges.
6.5 Find Expected Value MM1D2d: Use expected value to predict outcomes. Unit 4: The Chance of Winning!
Chapter 12 Section 1 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Chapter 5 Discrete Random Variables Probability Distributions
1 7.3 RANDOM VARIABLES When the variables in question are quantitative, they are known as random variables. A random variable, X, is a quantitative variable.
Lesson 7.8 Simple Probability Essential Question: How do you find the probability of an event?
Find Expected Value.  A collection of outcomes is partitioned into n events, no two of which have any outcomes in common. The probabilities of n events.
Introduction Imagine the process for testing a new design for a propulsion system on the International Space Station. The project engineers wouldn’t perform.
Simulations with Binomials Mean and S.D. of Binomials Section
Expected Value Standards: MM1D2. Students will use the basic laws of probability. d. Use expected value to predict outcomes. Lesson Essential Question:
Basic Probabilities Starting Unit 6 Today!. Definitions  Experiment – any process that generates one or more observable outcomes  Sample Space – set.
Chapter 6 Section 1 The Study of Randomness. How often would this method give a correct answer if I used it very many times? If we know the blood types.
16.6 Expected Value.
Larson/Farber Ch. 4 1 Elementary Statistics Larson Farber 4 x = number of on time arrivals x = number of points scored in a game x = number of employees.
11-2 Basic Probability.
Discrete Probability Distributions
Today is Tuesday.
Discrete Probability Distributions
AND.
Discrete Probability Distributions
Day 2 (same introduction)
The Nature of Probability
[4] the sum of the numbers you throw. It is your turn, you need to score exactly 4 to dice your score is the number you throw. If you throw two dice your.
Probability And Expected Value ————————————
L.O. Understand more about probability, using spinners.
Additional notes on random variables
11-2 Basic Probability.
A study of education followed a large group of fourth-grade children to see how many years of school they eventually completed. Let x be the highest year.
Warm-up $100 $100 90° 90° 60° 60° $200 60° $400 $300 If you spin once, what is the probability of getting each dollar amount (fractions)? 2) If you spin.
Probability And Expected Value ————————————
Additional notes on random variables
10-3 Probability distributions
Expected Value Lesson Essential Question:
Main Idea and New Vocabulary Key Concept: Probability
Bernoulli Trials Two Possible Outcomes Trials are independent.
6.5 Find Expected Value MM1D2d.
You can choose one of three boxes
Chapter 11 Probability.
Presentation transcript:

Expected Value MM1D2 Students will use the basic laws of probabilities. d. Use expected value to predict outcomes.

Expected Value Expected value E of the collection of outcomes is the sum of the products of the events’ probabilities and their values.

Expected Value The expected value or mean of a discrete distribution is the long-run average of occurrences. We must realize that any one trial using a discrete random variable yields only one outcome. However, if the process is repeated long enough, the average of the outcomes are most likely to approach a long-run average, expected value or mean value.

Spinner Game

Spinner Game

Spinner Game

Spinner Game

Spinner Game

Spinner Game

Try some… Consider a game in which two players each choose an integer from 1 to 3. If the sum of the two integers is even, then player A scores 4 points and player B loses 2 points. If the sum is odd, then player B scores 4 points and player A loses 2 points. Find the expected value for player A.

Answer The possible outcomes are 1+1 2+1 3+1 1+2 2+2 3+2 1+3 2+3 3+3 1+1 2+1 3+1 1+2 2+2 3+2 1+3 2+3 3+3 The probability of an even sum is 5/9. The probability of an odd sum is 4/9. Player A: E = 4(5/9) + (-2)(4/9) = 12/9 =4/3

Project Create a spinner for a game. Make sure you have at least seven sections distributed into semicircles and cut angles. Each spinner section needs to have numbers, dollar amounts, etc. Determine the expected value of 10 spins, 20 spins, and 50 spins.

Rubric Spinner Rubric Group members: 3 2 1 Construction The spinner was neatly constructed with evenly distributed parts. The spinner was neat but did not have evenly distributed numbers. The spinner was constructed but was not neat. Reasoning The problem was set up correctly with explanations given. Formulas were used. The problem was set up correctly with work shown. No work shown. Delivery All problems were correct with well written explanations. Less than 2 mistakes. 2 or more mistakes. Scale: 9 100 6 85 8 95 5 80 7 90 4 75 3 70