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Measuring Attractiveness By A Categorical Based Evaluation Technique (MACBETH)
Measuring attractiveness through a categorical-based evaluation technique (MACBETH)Bana e Costa CA, De Corte J-M, Vansnick J-C. MACBETH. International Journal of Information Technology & Decision Making. 2012;11(02):359–87.Bana e Costa CA, De Corte JM, Vansnick JC. On the mathematical foundations of MACBETH. In: Figueira J, Greco S, Ehrgott M, (Eds.) Multiple Criteria Decision Analysis: The State of the Art Surveys. New York: Springer; 2005. pp. 409–42.Bana e Costa CA, Chagas MP. A career choice problem: An example of how to use MACBETH to build a quantitative value model based on qualitative value judgments. European Journal of Operational Research. 2004;153(2):323–31. is a multiple-criteria decision analysis (MCDA) method that evaluates options against multiple criteria. MACBETH was designed by Carlos António Bana e Costa, from the University of Lisbon with Professor Jean-Claude Vansnick and Dr. Jean-Marie De Corte, from the Université de Mons. The key distinction bet ...
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International Journal Of Information Technology & Decision Making
The ''International Journal of Information Technology & Decision Making'' was founded in 2002 and is published by World Scientific. It is a peer-reviewed scientific journal covering the application of information technology to decision-making, in areas such as bio-informatics, fuzzy logic, neural networks, and online business. The current editor-in-chief is Yong Shi (College of Information Science and Technology, University of Nebraska, and CAS Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences The Chinese Academy of Sciences (CAS); ), known by Academia Sinica in English until the 1980s, is the national academy of the People's Republic of China for natural sciences. It has historical origins in the Academia Sinica during the Republi ...). Abstracting and indexing The journal is abstracted and indexed in Science Citation Index Expanded, CompuMath Citation Index, and Inspec. External links * {{DEFAULTSORT:International Journal of Inform ...
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Human Resource Management
Humans (''Homo sapiens'') are the most abundant and widespread species of primate, characterized by bipedalism and exceptional cognitive skills due to a large and complex brain. This has enabled the development of advanced tools, culture, and language. Humans are highly social and tend to live in complex social structures composed of many cooperating and competing groups, from families and kinship networks to political states. Social interactions between humans have established a wide variety of values, social norms, and rituals, which bolster human society. Its intelligence and its desire to understand and influence the environment and to explain and manipulate phenomena have motivated humanity's development of science, philosophy, mythology, religion, and other fields of study. Although some scientists equate the term ''humans'' with all members of the genus ''Homo'', in common usage, it generally refers to ''Homo sapiens'', the only extant member. Anatomically mode ...
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Medical Statistics
Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. However, "biostatistics" more commonly connotes all applications of statistics to biology. Medical statistics is a subdiscipline of statistics. "It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experien ...
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Mathematical Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maxima and minima, maximizing or minimizing a Function of a real variable, real function by systematically choosing Argument of a function, input values from within an allowed set and computing the Value (mathematics), value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, opti ...
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Mathematical And Quantitative Methods (economics)
Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics with the major subdisciplines of number theory, algebra, geometry, and analysis, respectively. There is no general consensus among mathematicians about a common definition for their academic discipline. Most mathematical activity involves the discovery of properties of abstract objects and the use of pure reason to prove them. These objects consist of either abstractions from nature orin modern mathematicsentities that are stipulated to have certain properties, called axioms. A ''proof'' consists of a succession of applications of deductive rules to already established results. These results include previously proved theorems, axioms, andin case of abstraction from naturesome basic properties that are considered true starting points of ...
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Regression Models
Regression or regressions may refer to: Science * Marine regression, coastal advance due to falling sea level, the opposite of marine transgression * Regression (medicine), a characteristic of diseases to express lighter symptoms or less extent (mainly for tumors), without disappearing totally * Regression (psychology), a defensive reaction to some unaccepted impulses * Nodal regression, the movement of the nodes of an object in orbit, in the opposite direction to the motion of the object Statistics * Regression analysis, a statistical technique for estimating the relationships among variables. There are several types of regression: ** Linear regression ** Simple linear regression ** Logistic regression ** Nonlinear regression ** Nonparametric regression ** Robust regression ** Stepwise regression * Regression toward the mean, a common statistical phenomenon Computing * Software regression, the appearance of a bug which was absent in a previous revision ** Regression testing, a s ...
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Single-equation Methods (econometrics)
A variety of methods are used in econometrics to estimate models consisting of a single equation. The oldest and still the most commonly used is the ordinary least squares method used to estimate linear regressions. A variety of methods are available to estimate non-linear models. A particularly important class of non-linear models are those used to estimate relationships where the dependent variable is discrete, truncated or censored. These include logit, probit and Tobit models. Single equation methods may be applied to time-series In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Exa ..., cross section or panel data. External links * Mathematical and quantitative methods (economics) {{econometrics-stub ...
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Design Of Experiments
The design of experiments (DOE, DOX, 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 control variables that must be h ...
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Decision Analysis
Decision analysis (DA) is the discipline comprising the philosophy, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision; for prescribing a recommended course of action by applying the maximum expected-utility axiom to a well-formed representation of the decision; and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker, and other corporate and non-corporate stakeholders. History In 1931, mathematical philosopher Frank Ramsey pioneered the idea of subjective probability as a representation of an individual’s beliefs or uncertainties. Then, in the 1940s, mathematician John von Neumann and economist Oskar Morgenstern developed an axiomatic basis for utility theory as a way of expressing an individual ...
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Sampling (statistics)
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population in question. Sampling has lower costs and faster data collection than measuring the entire population and can provide insights in cases where it is infeasible to measure an entire population. Each observation measures one or more properties (such as weight, location, colour or mass) of independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if ...
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Multiple-criteria Decision Analysis
Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (both in daily life and in settings such as business, government and medicine). Conflicting criteria are typical in evaluating options: cost or price is usually one of the main criteria, and some measure of quality is typically another criterion, easily in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider – it is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, managers are interested in getting high returns while simultaneously reducing risks; however, the stocks that have the potential of bringing high returns typically carry high risk of losing money. In a service industry, customer satisfaction and the cost of providing service are fundamen ...
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