Discrete Scenarios
In gambling and probability theory, there is usually a discrete set of possible outcomes. In this case, expected return is a measure of the relative balance of win or loss weighted by their chances of occurring.
For example, if a fair die is thrown and numbers 1 and 2 win $1, but 3-6 lose $0.5, then the expected gain per throw is
- E(R) = 1/3 × 1 - 2/3 × 0.5 = 0 .
Read more about this topic: Expected Return
Famous quotes containing the words discrete and/or scenarios:
“One can describe a landscape in many different words and sentences, but one would not normally cut up a picture of a landscape and rearrange it in different patterns in order to describe it in different ways. Because a photograph is not composed of discrete units strung out in a linear row of meaningful pieces, we do not understand it by looking at one element after another in a set sequence. The photograph is understood in one act of seeing; it is perceived in a gestalt.”
—Joshua Meyrowitz, U.S. educator, media critic. “The Blurring of Public and Private Behaviors,” No Sense of Place: The Impact of Electronic Media on Social Behavior, Oxford University Press (1985)
“The taste for worst-case scenarios reflects the need to master fear of what is felt to be uncontrollable. It also expresses an imaginative complicity with disaster.”
—Susan Sontag (b. 1933)