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The expected value with perfect information assumes that all states of nature are equally likely.

Question: The Expected Value With Perfect Information Assumes That All States Of Nature Are Equally Likely.Question 3 Options:TrueFalse This problem has been solved! See the answe The expected value with perfect information assumes that all states of nature are equally likely. False If a decision maker has to make a particular decision only once, expected monetary value is a good indication of the payoff associated with the decision The expected value with perfect information assumes that all states of nature are equally likely. False An example of expected monetary value would be the payoff from selecting a particular alternative when a particular state of nature occurs the expected value with perfect information assumes that all states of nature are equally alike a pessimist a decision maker who uses the maximin criterion when solving a problem under conditions of uncertainty is

The expected value of perfect information (EVPI) is the: The expected value with perfect information assumes that all states of nature are equally likely. Select one: True False. False. A decision tree is a(n): Select one •Assumes that all states of nature are equally likely to occur decision for that state of nature could be made •expected value with perfect information (EV w/ PI): the expected or average return if we have perfect information before a decision has to be made.

The expected value with perfect information assumes that all states of nature are equally likely. Free. when all states of nature are equally likely C) when all alternatives are equally likely D) under conditions of uncertainty E) under conditions of risk. The expected value with perfect information is A) the maximum EMV for a set of. States of Nature Alternatives Good Market Fair Market Poor Market Open 1 380,000 70,000 - 400,000 Open 2 200,000 80,000 - 200,000 Do Nothing 0 0 0 As Nick does not know how his product will be received, he assumes that all three states of nature are equally likely to occur The expected value of perfect information (EVPI) is used to measure the cost of uncertainty as the perfect information can remove the possibility of a wrong decision. The formula for EVPI is defined as follows: It is the difference between predicted payoff under certainty and predicted monetary value The expected value with perfect information assumes that all states of nature are equally likely. False (Types of decision-making environments, easy) 11. An example of expected monetary value would be the payoff from selecting a particular alternative when a particular state of nature occurs. False (Decision tables, moderate) 12

The Highest Value For The Equally Likely Criterions Is _____; This Occurs With Alternative _____. (1.5 Pts) States Of Nature Alternatives Option 1 S1 $10,000 S2 $30,000 Option 2 $5,000 $45,000 Option 3 $-4,000 $60,000 States Of Nature Alternatives S1 S2 P 0.6 0.4 Option 1 200 300 Option 2 50 350 2 Expected Value of Perfect Information (EVPI) DECISION TREES The equally likely approach assumes that each state of nature is equally likely to occur. Example A3 applies each of these approaches to the Getz Products Company. Maximax A criterion that finds a Assumes all outcomes equally likely and uses the average payoff Chose the large plant Alternatives No plant 0 Small plant 40,000 Expected Value of Perfect Information EVPI = EVwPI - EMV = $110,000 - $86,000 = $24,000 • The perfect information increases th

Expected value of perfect information = Rs. 100 . Thus, the inventory manager knows that the maximum amount that he would pay for a perfect prediction of demand would be Rs. 100. To pay more for perfect information than the loss that would result because of a lack of this information (uncer­tainty) would be irrational States of Nature Alternatives S 1 S 2 p.6.4 Option 1 200 300 Option 2 50 350 A) 0 B) 20 C) 50 D) 150 E) 200 Answer: B Diff: 3 Key Term: Expected value of perfect information (EVPI) AACSB: Analytic skills Objective: LO5 32) _____ is the criterion for decision making under uncertainty that finds an alternative that maximizes the minimum outcome 1. Assign equal p robability value to each state of nature by using the formula: 1 ÷ (number of states of nature) . 2. Compute the expected (or average) payoff for each alternative by adding all the payoffs and dividing by the number of possible states of nature. 3. Select the b est expected payoff value (maximum for profit ) 14.The expected value of perfect information is the same as the expected value with perfect information. False (Decision tables, moderate) 15.Decision trees and decision tables can both solve problems requiring a single decision, but decision tables are the preferred method when a sequence of decisions is involved 1) Expected monetary value (EMV) is the average or expected monetary outcome of a decision if it can be repeated a large number of times. 2) Expected monetary value (EMV) is the payoff you should expect to occur when you choose a particular alternative. 3) The decision maker can control states of nature. 4) All [

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The probabilities for states of nature A, B, and C are 0.3, 0.5, and 0.2, respectively. If a perfect forecast of the future were available, what is the expected value with this perfect information? A) 130. B) 160. C) 166. D) 36. E) None of the above. 52) The following is a payoff table giving profits for various situations Equally Likely (Laplace) 200,000 * 0.5 + (-180,000) * 0.5 = The equally likely approach assumes that all probabilities of occurrence for the states of nature are equal, and thus each state of nature is equally likely. 1

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Question: оооо Expected Monetary Value Is Most Appropriate For Problem Solving That Takes Place When Conditions Are Average When All States Of Nature Are Equally Likely When All Alternatives Are Equally Likely Under Conditions Of Risk 5 There Are Three Equally Likely States Of Nature Thich, Medium, And Low Demand). If The Large Factory Will Post Profits Of. Payoffs are profits. ch & $2400 de -$500 a) If P(1) - 0.19, then the expected value of ds, EV(da) is b) If the decision maker is indifferent between choosing d, and da, and P(1) -0.38, then the expected value of dy, EV(di) is c) If the missing EV(d) - $550, and P(s) - 0.37, then the better alternative is Odi och Od, or dh O 81 82 Osor 52 A. • Assumes that all states of nature are equally likely to probability assessments for all states of nature Q(action a) = (reward of 1st state of nature) X (probability of 1st state of nature) + (reward of 2nd state of nature) Expected Value of Perfect Information. Expected Value of Perfect If ti (In forma tion (EVPI) 1. Best alternative for favorable state of nature isBest alternative for favorable state of nature is build a large plant with a payoff of $200,000 Best alternative for unfavorable state of nature is to do nothing with a payoff of $0 So the maximum Thompson should pay for the additiona

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  1. Equally Likely Alternative State of Nature Row Average ($) Good Market ($) Average Market ($) Poor Market ($) 3 - 22 Construct a small plant 75,000 25,000 -40,000 20,000 Expected Value of Perfect Information ( EVPI ) Marketing research company can find out what the exact outcome will be - perfect information - decisio
  2. >Assume all states are equally likely S 1 2 3 D 1 10,000 6,500 -4,000 4,167 D 2 8,000 6,000 1,000 5,000 Decision D 3 5,000 (states of nature) >Expected value of perfect information (EVPI) is the increase in the expected profit that would result if one knew with certaint
  3. It assumes all the states of nature are equally likely to occur. The procedure to find an optimal decision. The Expected Value Criterion - spreadsheet 6.4 Expected Value of Perfect Information The gain in expected return obtained from knowing with certainty the future state of nature is called: Expected Value of Perfect Information (EVPI.

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Standard Laplace indicates that the decision maker is assumed that the probability of occurrence of different nature are equal situations, so it made the comparison on the basis of the best expected values, so choose the alternative that achieves the highest profit when comparing profits and alternative that achieves the lowest results when comparing cost Strategy A has an expected value of 10 and a standard deviation of 3. Strategy B has an expected value of 10 and a standard deviation of 5. c. states of nature. d. the marginal utility of money. One reason is that a person with health insurance is less likely to take precautions that will prevent illness. This is an example of The following is a payoff table giving profits for various situations. 11eab9ea_e5c1_f1ec_b53a_8de98db5ba88_TB5481_00 The probabilities for states of nature A, B, and C are 0.3, 0.5, and 0.2, respectively.If a perfect forecast of the future were available, what is the expected value with this perfect information? A)130 B)160 C)166 D)3

is equal to the highest expected payoff; is greater than the expected value with perfect information; is equal to the expected value of perfect information ; is computed when finding the minimax regret decision. In using the criterion of realism (Hurwicz criterion), the coefficient of realism . is the probability of a good state of nature - It assumes all the states of nature are equally likely to occur. Expected Value of Perfect Information • The gain in expected return obtained from knowing with certainty the future state of nature is called: Expected Value of Perfect Information (EVPI) 34 EVPI 36 The Expected Value of Perfect Information Decision Large rise Small. The equal likelihood, or LaPlace, criterion weights each state of nature equally, thus assuming that the states of nature are equally likely to occur. The equal likelihood criterion multiplies the decision payoff for each state of nature by an equal weight

Expected Monetary Value (EMV) Expected monetary value (EMV) is the sum of the payoffs for each course of action multiplied by the probabilities associated with each state of nature. 20. Example Suppose that in Previous Example, the probability of occurrence of various states of nature are also provided as indicated in Table below Laplace (equally likely decision) criterion. Maximin or minimax criterion. Maximax or minimin criterion. Hurwicz criterion. Regret criterion. 2. Explain the following criterions of decision making under risk: Expected monetary value (EMV) Expected opportunity loss (EOL) Expected value of perfect information (EVPI It assumes all the states of nature are equally likely to occur. The procedure to find an optimal decision. spreadsheet 6.4 Expected Value of Perfect Information The gain in expected return obtained from knowing with certainty the future state of nature is called: Expected Value of Perfect Information (EVPI) TOM BROWN - EVPI TOM BROWN. In probability theory, the expected value of a random variable, denoted ⁡ or ⁡ [], is a generalization of the weighted average, and is intuitively the arithmetic mean of a large number of independent realizations of .The expected value is also known as the expectation, mathematical expectation, mean, average, or first moment.Expected value is a key concept in economics, finance, and many. Answer 0.5-0.5 0.0625 There is insufficient information to answer the question. None of these 4 points Question 11 1. Consider the following payoff table. How much should be paid for a perfect forecast of the state of nature? Answer 170 30 10 100 40 4 points Question 12 1

1. For Problem 19C1, use expected value of perfect information (EVPI) to select the best act. Probabilities of different events given in problem 19C1 can be used to apply expected value of perfect information (EVPI). 2. What are the various elements of decision analysis? 3. Explain the difference.. The expected gain is the expected value of perfect information or EVPI. 32. Example: Compute for the expected payoff under certainty. The best payoff for the small capacity and large capacity are P370 and P900 respectively. Then combine by weighing each payoff by the probability of that state of nature and add the amounts

risk, we think we know the probabilities Of the states Of nature, while under uncertainty we do not know the probabilities Of the states Of nature. 6) E V PI (expected value Of perfect information) is a measure Of the maximum EMV as a result Of additional information d. equally likely criterion. front 5. equal to the expected value of perfect information b. greater than the expected value with perfect information. c. equal to the expected value of perfect information. d. computed when finding the minimax regret decision a. is the probability of a good state of nature. b. describes the degree of. This assumes that the investor is neutral and that the decision payoff of each state of nature is equally likely to occur and as such are weighted equally. Apartment Building . $ 50,000(0.5) + $30,000(0.5) = $40,000 The expected value of perfect information equals the expected opportunity loss for the best decision Next, determine the expected payoff for each alternative across each state of nature under risk Then determine the best expected payoff (EMV) EVPI = Expected value of = Expected payoff - Expected payoff perfect information under certainty under risk = 12.2 - 10.5 = 1.7 Finally, determine EVPI using expected payoff Assumes States of Nature Equally Likely Payoff with Perfect Information and the Expected Payoff Under Risk Your Expected Value is Negative No Yes Buy Raffle Ticket? $0 -$0.

The probability of low demand is 0.4, whereas the probability of medium and high demand is each 0.3. a) What is the highest possible expected monetary value? b) Calculate the expected value of perfect information for this situation. A.27 Given the following conditional value table, determine the appropriate decision assuming that each state of nature has an equal likelihood of occurring A state of nature is an actual event that may occur in the future. states of nature are equally likely . to occur. Decision Values Apartment building $50,000(.5) + 30,000(.5) = 40,000. EVPI equals the expected value given perfect information DECESION MAKING UNDER RISK:<br />Here more than one state of nature exists and the decision maker has sufficient information to assign probabilities to each of these states. <br />These probabilities could be obtained from the past records or simply the subjective judgment of the decision maker. <br />Under conditions of risk, knowing the.

The states of nature are the states of economy during, an arbitrary time frame, as in one year. The expected value (i.e., the averages) is defined by: Expected Value = m = SX i. P i, the sum is over all i's. The expected value alone is not a good indication of a quality decision. The variance must be known so that an educated decision may be made Expected value is the probability weighted average. Expected value and simple average are the same if the probabilities for all states of nature are equal. Expected value is the sum of multiplying each possible outcome by the probability of occurrence. In the above example assuming an equally likely chance of gettin The expected value can really be thought of as the mean of a random variable. This means that if you ran a probability experiment over and over, keeping track of the results, the expected value is the average of all the values obtained. The expected value is what you should anticipate happening in the long run of many trials of a game of chance 1. The decision maker can control states of nature. True False 2. The difference in Decision Making Under Risk and decision making under uncertainty is that under risk, we think we know the probabilities of the states of nature, while under uncertainty we do not know the probabilities of the states of nature. True False 3. To determine the effect of input changes on decision results, we should. value of perfect information, expected value of sample information, cost of irrationality, marginal analysis, sequential decision making, normal distribution. It is not that the different states of nature are equally likely to occur. For example, state I could be present conditions prevailing at that time; state II could be some economic.

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The probabilities for states of nature A, B, and C are 0.3, 0.5, and 0.2, respectively. If a person selected Alternative 1, what would the expected profit be? A)120 B)180 C)133.33 D)126 E)None of the above 13) 14)The equally likely criterion is also called the _____ criterion. A)Huchenmeizer B)Laplace C)LaFlore D)Hurwicz E)uncertainty 14) A- EVPI = EVwPI −Maximum EMV without perfect information = $60,000 So the maximum Thompson should pay for the additional information is $60,000. Thompson should not pay $65,000 for this information! Expected Value of Perfect Information (EVPI) (5 of 5) EVwPI = ∑(best payoff in state of nature i) (probability of state of nature i Expected Value of Perfect Information (EVPI ) STATE OF NATURE ALTERNATIVE FAVORABLE MARKET ($) UNFAVORABLE MARKET ($) EMV ($) Construct a large plant 200,000 -180,000 10,000 Construct a small plant 100,000 -20,000 40,000 Do nothing 0 0 0 With perfect information 200,000 0 100,000 Probabilities 0.5 0.5 Table 3.10 EVwPI Decision Table with.

states of nature are equally likely . to occur. Decision Making without Probabilities. Equal Likelihood Criterion. Decision: Values; EVPI equals the expected value given perfect information minus the expected value without perfect information. EVPI equals the . expected opportunity loss (EOL) for the best decision Expected value (EV) is a concept employed in statistics to help decide how beneficial or harmful an action might be. Knowing how to calculate expected value can be useful in numerical statistics, in gambling or other situations of probability, in stock market investing, or in many other situations that have a variety of outcomes The Efficient Market Hypothesis assumes all stocks trade at their fair value. The weak tenet implies stock prices reflect all available information, the semi-strong implies stock prices are. Probability Revisions Given a Favorable Survey Conditional Probability Posterior Probability State of Nature P(Survey positive|State of Nature Prior Probability Joint Probability FM 0.70 * 0.50 0.35 0.45 0.35 = 0.78 UM 0.20 * 0.50 0.45 0.10 0.10 = 0.22 0.45 1.00 Probability Revisions Given an Unfavorable Survey Conditional Probability Posterior.

Consider the following payoff table States of Nature

Expected Monetary Value (EMV). The EMV determines the best expected payoff across all states of nature Decision Trees 04 - 23 S t a t e o f n a t u r e 1 Initial Decision Payoff 1 State of n at ure 2 Payoff 2 Payoff 3 2 C h o s e A ' 1 Ch ose A' 2 Payoff 6 State of n at ure 2 2 Payoff 4 Payoff 5 C h o s e A ' 3 Ch ose A' 4 S t a t. Assume that only three states of nature are possible for tomorrow's weather: fair, overcast, and precipitation (rain, snow, sleet or hail). Rank order the states of nature in terms of their likelihood of occurrence as perceived by you, subjectively, with the most likely state heading the list and the least likely state at the bottom Since I don't know anything about the nature, every state of nature is equally likely to occur: a) For each state of nature, use an equal probability (i.e., a Flat Probability), b) Multiply each number by the probability, c) Add action rows and put the sum in the Expected Payoff column, d) Choose largest number in step (c) and perform that action

< preferred alternative w/o perfect information < preferred alternative w/o perfect information $0.00 $30.00 10.50 < preferred alternative w/o perfect information 0.65 0.35 1.00 50.00 30.00 43.00 14.00 Expected Value of Perfect Information This value represents the optimal payoff that could be achieved if we knew with certainty that state of. The CAPM also assumes that the risk-free rate will remain constant over the discounting period. Assume in the previous example that the interest rate on U.S. Treasury bonds rose to 5% or 6% during. The probability of each of these values is 1/6 as they are all equally likely to be the value of Z. For instance, the probability of getting a 3, or P (Z=3), when a die is thrown is 1/6, and so is. Decison making under risk where you are you are not only aware about the various states of nature but also you have probability estimates for these states of nature. In this situation how you can make decison using expected monetary value approach. This course also talk about decison tree. It's non-technical

One view is that all proteins in the database are a priori equally likely to be related to the query. This implies that a low E -value for an alignment involving a short database sequence should carry the same weight as a low E -value for an alignment involving a long database sequence Expected Value With Perfect Information (EVPI) EVPI = Expected Payoff - Maximum expected payoff under Certainty with no information Let N: Number of states of nature and k: Number of actions, ∑ N www.themegallery.com 2233 { }) .Pj j=1 (Max i X ij EVPI places an upper bound on what one would pay foradditional information • It assumes all the states of nature are equally likely to occur. • The procedure to find an optimal decision. - For each decision add all the payoffs. - Select the decision with the largest sum (for profits). Teknik Informatika - UTAMA Sistem Pendukung Keputusan 38 The Principle of Insufficient Reason • Sum of Payoffs - Gold 50 the expected value of perfect information (EVPI) Evaluate. the nodes in a decision tree. Assumes each state of nature is equally likely to occur. TABLE A.2. Equally likely. Decision Making Under Risk. Each possible state of nature has an assumed probability

Expected Value of Perfect Information (EVPI) Decision Table with Perfect Information STATE OF NATURE ALTERNATIVE FAVORABLE MARKET ($) UNFAVORABLE MARKET ($) EMV ($) Construct a large plant 200,000 -180,000 10,000 Construct a small plant 100,000 -20,000 40,000 Do nothing 0 0 0 With perfect information 200,000 0 100,000 Probabilities 0.5 0. The Expected Value of Perfect Information (EVPI) The Expected Value under Certainty is simply the sum of the best expected payoffs under each state of nature. Expected Value under Certainty = 0.1×270+0.6×180+0.3×90 = 27+108+27 = 162. The Maximum Expected Monetary Value we already calculated as Max EMV= 147 DEFINITION. EVPI (Expected Value of Perfect Information) is defined as following: EVPI = Best Outcome for State i* P[X=xi] - EMV. From the above example, we have: EVPI = 200/2 +0/2 - 40 = 60. Thus the most Thompson would be willing to pay for perfect information is 60$. OPPORTUNITY LOSS

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