Utility Assessment

	Utility Assessment Utility assessment, also called utility measurement, is a process by which the utility function of individuals or groups can be estimated. There are many different methods for utility assessment. Assessing single-attribute utility functions A single-attribute utility function maps the amount of money a person has (or gains), to a number representing the subjective satisfaction he derives from it. The motivation to define a utility function comes from the St. Petersburg paradox: the observation that people are not willing to pay much for a lottery, even if its expected monetary gain is infinite. The classical solution to this paradox, suggested by Daniel Bernoulli and Gabriel Cramer, is that most people have a utility function that is strictly concave, and they aim to maximize their expected utility, rather than their expected gain. Power-log utility Bernouli himself assumed that the utility is logarithmic, that is, u(''x'')=log(''x'') where x is the amount of money; this was s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Utility Function In economics, utility is a measure of a certain person's satisfaction from a certain state of the world. Over time, the term has been used with at least two meanings. * In a Normative economics, normative context, utility refers to a goal or objective that we wish to maximize, i.e., an objective function. This kind of utility bears a closer resemblance to the original Utilitarianism, utilitarian concept, developed by moral philosophers such as Jeremy Bentham and John Stuart Mill. * In a Positive economics, descriptive context, the term refers to an ''apparent'' objective function; such a function is Revealed preference, revealed by a person's behavior, and specifically by their preferences over Lottery (decision theory), lotteries, which can be any quantified choice. The relationship between these two kinds of utility functions has been a source of controversy among both Economics, economists and Ethics, ethicists, with most maintaining that the two are distinct but generally re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Confounding In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.Pearl, J., (2009). Simpson's Paradox, Confounding, and Collapsibility In ''Causality: Models, Reasoning and Inference'' (2nd ed.). New York : Cambridge University Press. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system. Confounders are threats to internal validity. Example Let's assume that a trucking company owns a fleet of trucks made by two different manufacturers. Trucks made by one manufacturer are called "A Trucks" and trucks made by the other manufacturer are called "B Trucks." ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Experimental Design The design of experiments (DOE), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Discrete Choice In economics, discrete choice models, or qualitative choice models, describe, explain, and predict choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be a continuous variable. In the continuous case, calculus methods (e.g. first-order conditions) can be used to determine the optimum amount chosen, and demand can be modeled empirically using regression analysis. On the other hand, discrete choice analysis examines situations in which the potential outcomes are discrete, such that the optimum is not characterized by standard first-order conditions. Thus, instead of examining "how much" as in problems with continuous choice variables, discrete choice analysis examines "which one". However, discrete choice analysis can also be used to examine the chosen quantity when only a few distinc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]