Expected Value. When faced with uncertainties, decisions are usually not based solely on probabilities A building contractor has to decide whether to.

Slides:



Advertisements
Similar presentations
1/2, 1/6, 1/6, 1/6 1)If you spin once, what is the probability of getting each dollar amount (fractions)? 2) If you spin twice, what is the probability.
Advertisements

Economics of Information (ECON3016)
Discrete Distributions
Section 6.3 ~ Probabilities With Large Numbers
At a particular carnival, there is a dice game that costs $5 to play. -If the die lands on an odd number, you lose. -If the die lands on a 2 or 4, you.
Discrete Probability Distributions
Review and Preview and Random Variables
Clear your desk for your quiz. Unit 2 Day 8 Expected Value Average expectation per game if the game is played many times Can be used to evaluate and.
Random Variables. Definitions A random variable is a variable whose value is a numerical outcome of a random phenomenon,. A discrete random variable X.
Excursions in Modern Mathematics, 7e: Copyright © 2010 Pearson Education, Inc. 16 Mathematics of Managing Risks Weighted Average Expected Value.
Take out a coin! You win 4 dollars for heads, and lose 2 dollars for tails.
Warm up 1)We are drawing a single card from a standard deck of 52 find the probability of P(seven/nonface card) 2)Assume that we roll two dice and a total.
Chapter 5 Understanding Randomness
Probability.
Probability Distributions Finite Random Variables.
Expected Value- Random variables Def. A random variable, X, is a numerical measure of the outcomes of an experiment.
Conditional Probability.  A newspaper editor has 120 letters from irate readers about the firing of a high school basketball coach.  The letters are.
Probability And Expected Value ————————————
Random Variables A Random Variable assigns a numerical value to all possible outcomes of a random experiment We do not consider the actual events but we.
Expected Value.  In gambling on an uncertain future, knowing the odds is only part of the story!  Example: I flip a fair coin. If it lands HEADS, you.
Chapter 7 Expectation 7.1 Mathematical expectation.
Chapter 14 sec 4 Expected Value. Questions How many of you have car insurance? How many of you have health insurance? Do you wonder how the insurance.
Lottery Problem A state run monthly lottery can sell 100,000tickets at $2 a piece. A ticket wins $1,000,000with a probability , $100 with probability.
What are the chances of that happening?. What is probability? The mathematical expression of the chances that a particular event or outcome will happen.
Copyright ©2005 Brooks/Cole, a division of Thomson Learning, Inc. Understanding Probability and Long-Term Expectations Chapter 16.
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.
Copyright ©2005 Brooks/Cole, a division of Thomson Learning, Inc. Understanding Probability and Long-Term Expectations Chapter 16.
Jon Curwin and Roger Slater, QUANTITATIVE METHODS: A SHORT COURSE ISBN © Thomson Learning 2004 Jon Curwin and Roger Slater, QUANTITATIVE.
Please turn off cell phones, pagers, etc. The lecture will begin shortly.
Chapter 5: Probability Distribution What is Probability Distribution? It is a table of possible outcomes of an experiment and the probability of each outcome.
Chapter 5 Discrete Probability Distributions Lecture 1 Sections: 5.1 – 5.2.
Probability Distributions Random Variables * Discrete Probability Distributions * Mean, Variance, and Standard Deviation * Expected Value.
Conditional Probability.  So far for the loan project, we know how to: Compute probabilities for the events in the sample space: S = {success, failure}.
1 MAT116 Chapter 4: Expected Value : Summation Notation  Suppose you want to add up a bunch of probabilities for events E 1, E 2, E 3, … E 100.
Copyright © 2011 Pearson Education, Inc. Probability: Living with the Odds Discussion Paragraph 7B 1 web 59. Lottery Chances 60. HIV Probabilities 1 world.
DISCRETE PROBABILITY DISTRIBUTIONS
Choice under uncertainty Assistant professor Bojan Georgievski PhD 1.
Expected Value.
MM1D2d: Use expected value to predict outcomes
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Learning Objectives for Section 8.5 The student will be able to identify what is meant by a random variable.
7.2 Means and variances of Random Variables (weighted average) Mean of a sample is X bar, Mean of a probability distribution is μ.
Probability Evaluation 11/12 th Grade Statistics Fair Games Random Number Generator Probable Outcomes Resources Why Fair Games? Probable Outcome Examples.
Decision theory under uncertainty
Not So Great Expectations! Which game do you think has the highest return per dollar?
MM207 Statistics Welcome to the Unit 7 Seminar With Ms. Hannahs.
Discrete Distributions. Random Variable - A numerical variable whose value depends on the outcome of a chance experiment.
WOULD YOU PLAY THIS GAME? Roll a dice, and win $1000 dollars if you roll a 6.
L56 – Discrete Random Variables, Distributions & Expected Values
Chapter 5 Discrete Random Variables Probability Distributions
The Mean of a Discrete Random Variable Lesson
Properties of the Binomial Probability Distributions 1- The experiment consists of a sequence of n identical trials 2- Two outcomes (SUCCESS and FAILURE.
Copyright © 2011 Pearson Education, Inc. Probability: Living with the Odds Discussion Paragraph 7B 1 web 59. Lottery Chances 60. HIV Probabilities 1 world.
1 Chapter 4 Mathematical Expectation  4.1 Mean of Random Variables  4.2 Variance and Covariance  4.3 Means and Variances of Linear Combinations of Random.
Copyright © 2009 Pearson Education, Inc. 6.3 Probabilities with Large Numbers LEARNING GOAL Understand the law of large numbers, use this law to understand.
Probability Distributions. Constructing a Probability Distribution Definition: Consists of the values a random variable can assume and the corresponding.
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.
Week 5 Discrete Random Variables and Probability Distributions Statistics for Social Sciences.
Lesson 96 – Expected Value & Variance of Discrete Random Variables HL2 Math - Santowski.
Expected Value.
Random Variable, Probability Distribution, and Expected Value
Chapter 16.
Probability And Expected Value ————————————
Probability Key Questions
Discrete Distributions
Probability And Expected Value ————————————
Discrete Distributions
Discrete Distributions.
Discrete Distributions
Sets, Combinatorics, Probability, and Number Theory
Presentation transcript:

Expected Value

When faced with uncertainties, decisions are usually not based solely on probabilities A building contractor has to decide whether to bid on a construction job: 20% chance of a $40,000 profit 80% chance of a $9,000 loss Do we bid on the contract?

Expected Value The chances for a profit are not very high but we stand to gain more than we stand to lose How do we combine probabilities and consequences?

Expected Value Consider the following: A person aged 22 can expect to live 51 more years A married woman can expect to have 2.4 children A person can expect to eat 10.4 pounds of cheese and 324 eggs in a year What do we mean we say expect?

Expected Value Mathematical expectation can be interpreted as an average A person aged 22 can expect to live an average of 51 more years A married woman can expect to have an average of 2.4 children A person can expect to eat an average of 10.4 pounds of cheese and 324 eggs in a year

Expected Value Ex: Suppose there are 1000 raffle tickets. There is a $500 prize for the winning ticket and a consolation prize of $1.00 for all other tickets. How much can a person expect to win playing the raffle?

Expected Value Sol: Suppose all 1000 tickets are drawn and each persons winnings was recorded. What would a persons average winnings be? Notice this is the probability of getting the winning ticket Notice this is the probability of not getting the winning ticket

Expected Value The last slide tells us several things: Each amount won has a probability associated with it The amount won is multiplied by its respective probability The sum of the products is the expected value Expected value is a weighted average (if we run the experiment many times, what is the average)

Expected Value What is a weighted average? Ex: A student computes his average grade in a course in which he took six exams: 75, 90, 75, 87, 75, and 90. He computes his average score as follows:

Expected Value Notice he can also write the same average as: The average is the weighted average of the students grade, each grade being weighted by the probability the grade occurs

Expected Value Our raffle ticket example showed each amount had a probability associated with it We did NOT consider the actual events but we associate numbers with the events that arose from the experiment

Expected Value A Random Variable assigns a numerical value to all possible outcomes of a random experiment Ex: # of heads you get when you flip a coin twice The sum you get when you roll two dice

Expected Value Ex. Consider tossing a coin 4 times. Let X be the number of heads. Find and.

Expected Value Soln.

Expected Value Note that the notation asks for the probability that the random variable represented by X is equal to a value represented by x. Remember that for n distinct outcomes for X, (The sum of all probabilities equals 1).

Expected Value Formula for expected value (for n distinct outcomes: Expected value of the random variable X

Expected Value Ex. Find the expected value of X where X is the number of heads you get from 4 tosses. Assume the probability of getting heads is 0.5. Soln. First determine the possible outcomes. Then determine the probability of each. Next, take each value and multiply it by its respective probability. Finally, add these products.

Expected Value Possible outcomes: 0, 1, 2, 3, or 4 heads Probability of each:

Expected Value Take each value and multiply it by its respective probability: Add these products = 2

Expected Value Ex. A state run monthly lottery can sell 100,000 tickets at $2 apiece. A ticket wins $1,000,000 with probability , $100 with probability 0.008, and $10 with probability On average, how much can the state expect to profit from the lottery per month?

Expected Value Soln. States point of view: Earn:Pay:Net: $2 $1,000,000 -$999,998 $2$100 -$98 $2$10 -$8 $2 $0 $2 These are the possible values. Now find probabilities

Expected Value Soln. States point of view: We get the last probability since the sum of all probabilities must add to 1.

Expected Value Soln. States point of view: Finally, add the products of the values and their probabilities

Expected Value Focus on the Project: X: amount of money from a loan work out Compute the expected value for typical loan:

Expected Value Focus on the Project: What does this tell us? Foreclosure: $2,100,000 Ave. loan work out: $1,991,000 Tentatively, we should foreclose. This doesnt account for the specific characteristics of J. Sanders. However, this could reinforce or weaken our decision.