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The expected value criterion is also called the Bayesian principle. Maximax (Optimist) The maximax looks at the best that could happen under each action and then chooses the action with the largest value. They assume that they will get the most possible and then they take the action with the best best case scenario.

Expected opportunity loss (EOL) is a statistical calculation used primarily in the business field to help determine optimal courses of action. ... Calculating the EOL is an organized way of using a mathematical model to compare these choices and outcomes, to make the most profitable decision.

Expected monetary value (EMV) is a risk management technique to help quantify and compare risks in many aspects of the project. EMV is a quantitative risk analysis technique since it relies on specific numbers and quantities to perform the calculations, rather than high-level approximations like high, medium and low.Jan 7, 2015

Value derived by multiplying the consequence associated with the optimal act under each possible state of nature by the probability associated with that state of nature and summing the products.

• Expected value is a calculation in probability. In statistics and probability, the formula for expected value is E(X) = summation of X * P(X), or the sum of all gains multiplied by their individual probabilities.

• Expected value of sample information. In decision theory, the expected value of sample information (EVSI) is the expected increase in utility that a decision-maker could obtain from gaining access to a sample of additional observations before making a decision.

• Expected value uses probabilities to determine what an expected outcome, such as a payoff, will be. Expected value multiplies the probability of each outcome by the possible outcome. For example, in a dice game, rolling a one, three or five pays $0, rolling a two or four pays $5, and rolling a six pays $10.

• Expected value. The formal definition subsumes both of these and also works for distributions which are neither discrete nor absolutely continuous; the expected value of a random variable is the integral of the random variable with respect to its probability measure.

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. It is the difference between predicted payoff under certainty and predicted monetary value.

The expected value of sample information can never be less than the expected value of perfect information. The minimum expected opportunity loss provides the best decision, regardless of whether the decision analysis involves minimization or maximization.

Imperfect information is not as valuable as perfect information. The value of information (either perfect or imperfect) may be calculated as follows: Expected Profit (Outcome) WITH the information LESS Expected Profit (Outcome) WITHOUT the information

The expected value approach is more appropriate for a one-time decision than a repetitive decision. Maximizing the expected payoff and minimizing the expected opportunity loss result in the same recommended decision. The expected value of sample information can never be less than the expected value of perfect information.