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Plackett–Burman Design
Plackett–Burman designs are experimental designs presented in 1946 by Robin L. Plackett and J. P. Burman while working in the British Ministry of Supply. Their goal was to find experimental designs for investigating the dependence of some measured quantity on a number of independent variables (factors), each taking ''L'' levels, in such a way as to minimize the variance of the estimates of these dependencies using a limited number of experiments. Interactions between the factors were considered negligible. The solution to this problem is to find an experimental design where ''each combination'' of levels for any pair of factors appears the ''same number of times'', throughout all the experimental runs (refer to table). A complete factorial design would satisfy this criterion, but the idea was to find smaller designs. For the case of two levels (''L'' = 2), Plackett and Burman used the method found in 1933 by Raymond Paley for generating orthogonal matrices whose eleme ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Experimental Design
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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Raj Chandra Bose
Raj Chandra Bose (19 June 1901 – 31 October 1987) was an Indian American mathematician and statistician best known for his work in design theory, finite geometry and the theory of error-correcting codes in which the class of BCH codes is partly named after him. He also invented the notions of partial geometry, association scheme, and strongly regular graph and started a systematic study of difference sets to construct symmetric block designs. He was notable for his work along with S. S. Shrikhande and E. T. Parker in their disproof of the famous conjecture made by Leonhard Euler dated 1782 that there do not exist two mutually orthogonal Latin squares of order 4''n'' + 2 for every ''n''. Early life Bose was born in Hoshangabad, India; he was the first of five children. His father was a physician and life was good until 1918 when his mother died in the influenza pandemic. His father died of a stroke the following year. Despite difficult circumstances, Bose con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Block Design
In combinatorial mathematics, a block design is an incidence structure consisting of a set together with a family of subsets known as ''blocks'', chosen such that frequency of the elements satisfies certain conditions making the collection of blocks exhibit symmetry (balance). They have applications in many areas, including experimental design, finite geometry, physical chemistry, software testing, cryptography, and algebraic geometry. Without further specifications the term ''block design'' usually refers to a balanced incomplete block design (BIBD), specifically (and also synonymously) a 2-design, which has been the most intensely studied type historically due to its application in the design of experiments. Its generalization is known as a t-design. Overview A design is said to be ''balanced'' (up to ''t'') if all ''t''-subsets of the original set occur in equally many (i.e., ''λ'') blocks. When ''t'' is unspecified, it can usually be assumed to be 2, which means that ea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fractional Factorial Design
In statistics, fractional factorial designs are experimental designs consisting of a carefully chosen subset (fraction) of the experimental runs of a full factorial design. The subset is chosen so as to exploit the sparsity-of-effects principle to expose information about the most important features of the problem studied, while using a fraction of the effort of a full factorial design in terms of experimental runs and resources. In other words, it makes use of the fact that many experiments in full factorial design are often redundant, giving little or no new information about the system. Notation Fractional designs are expressed using the notation ''l''k − p, where ''l'' is the number of levels of each factor investigated, ''k'' is the number of factors investigated, and ''p'' describes the size of the fraction of the full factorial used. Formally, ''p'' is the number of ''generators'', assignments as to which effects or interactions are ''confounded'', ''i.e.'', ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Box–Behnken Design
In statistics, Box–Behnken designs are experimental designs for response surface methodology, devised by George E. P. Box and Donald Behnken in 1960, to achieve the following goals: * Each factor, or independent variable, is placed at one of three equally spaced values, usually coded as −1, 0, +1. (At least three levels are needed for the following goal.) * The design should be sufficient to fit a quadratic model, that is, one containing squared terms, products of two factors, linear terms and an intercept. * The ratio of the number of experimental points to the number of coefficients in the quadratic model should be reasonable (in fact, their designs kept in the range of 1.5 to 2.6). * The efficiency (statistics), estimation variance should more or less depend only on the distance from the centre (this is achieved exactly for the designs with 4 and 7 factors), and should not vary too much inside the smallest (hyper)cube containing the experimental points. (See "rotatability" i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Indian Agricultural Statistics Research Institute
The Indian Agricultural Statistics Research Institute is an institute under the Indian Council of Agricultural Research (ICAR) with the mandate for developing new techniques for the design of agricultural experiments as well as to analyze data in agriculture. The institute is affiliated with and is located in the campus of the Indian Agricultural Research Institute, a deemed university, at Pusa in New Delhi. The institute includes sections that specialize in statistical techniques for animal and plant breeding, bioinformatics, sampling, experimental design, modelling and forecasting. Origin and history In 1930 the, then, Imperial Council of Agricultural Research, started a statistical unit to assist the State Departments of Agriculture and Animal Husbandry in planning their experiments, analysis of experimental data, interpretation of results and rendering advice on the formulation of the technical programmes of the Council. This unit was established on the recommendation of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Technometrics
Technometrics is a journal of statistics for the physical, chemical, and engineering sciences, published quarterly since 1959 by the American Society for Quality and the American Statistical Association. Statement of purpose The purpose of ''Technometrics'' is to contribute to the development and use of statistical methods in physical, chemical, and engineering sciences as well as information sciences and technology. This vision includes developments on the interface of statistics and computer science such as data mining, machine learning, large databases, and so on. The journal places a premium on clear communication among statisticians and practitioners of these sciences and an emphasis on the application of statistical concepts and methods to problems that occur in these fields. The journal will publish papers describing new statistical techniques, papers illustrating innovative application of known statistical methods, expository papers on particular statistical methods, and pa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Confounding
In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) 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. Confounds are threats to internal validity. Definition Confounding is defined in terms of the data generating model. Let ''X'' be some independent variable, and ''Y'' some dependent variable. To estimate the effect of ''X'' on ''Y'', the statistician must suppress the effects of extraneous variables that influence both ''X'' and ''Y''. We say that ''X'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Alias (statistics)
Alias may refer to: * Pseudonym, a fictitious name that a person or group assumes for a particular purpose ** Pen name, a pseudonym adopted by an author and printed on the title page or by-line of their works in place of their real name ** Stage name, a pseudonym used by performers and entertainers * Nickname, a substitute for the proper name of a familiar person, place or thing * Code name, a code word or name used, sometimes clandestinely, to refer to another name, word, project, or person Arts and entertainment Film and television * ''Alias'' (2013 film), a 2013 Canadian documentary film * ''Alias'' (TV series), an American action thriller series 2001–2006 * ''Alias the Jester'', a 1995 British animated series * ''Alias – the Bad Man'', a 1931 American Western film Gaming * ''Alias'' (board game) * Alias (''Forgotten Realms''), a fictional character in ''Dungeons & Dragons'' * ''Alias'' (video game), 2004, based on the TV series Literature * ''Alias'' (comics), a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sankhya (journal)
''Sankhyā: The Indian Journal of Statistics'' is a quarterly peer-reviewed scientific journal on statistics published by the Indian Statistical Institute (ISI). It was established in 1933 by Prasanta Chandra Mahalanobis, founding director of ISI, along the lines of Karl Pearson's ''Biometrika''. Mahalanobis was the founding editor-in-chief. Each volume of ''Sankhya'' consists of four issues, two of them are in Series A, containing articles on theoretical statistics, probability theory, and stochastic processes, whereas the other two issues form Series B, containing articles on applied statistics, i.e. applied probability, applied stochastic processes, econometrics, and statistical computing. ''Sankhya'' is considered as "core journal" of statistics by the Current Index to Statistics. Publication history ''Sankhya'' was first published in June 1933. In 1961, the journal split into two series: Series A which focused on mathematical statistics and Series B which focused on stat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Indian Statistical Institute
Indian Statistical Institute (ISI) is a higher education and research institute which is recognized as an Institute of National Importance by the 1959 act of the Indian parliament. It grew out of the Statistical Laboratory set up by Prasanta Chandra Mahalanobis in Presidency College, Kolkata. Established in 1931, this unique institution of India is one of the oldest institutions focused on statistics, and its early reputation led it to being adopted as a model for the first US institute of statistics set up at the Research Triangle, North Carolina by Gertrude Mary Cox. Mahalanobis, the founder of ISI, was deeply influenced by the wisdom and guidance of Rabindranath Tagore and Brajendranath Seal. Under his leadership, the institute initiated and promoted the interaction of statistics with natural and social sciences to advance the role of statistics as a key technology by explicating the twin aspectsits general applicability and its dependence on other disciplines for its own d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fractional Factorial Design
In statistics, fractional factorial designs are experimental designs consisting of a carefully chosen subset (fraction) of the experimental runs of a full factorial design. The subset is chosen so as to exploit the sparsity-of-effects principle to expose information about the most important features of the problem studied, while using a fraction of the effort of a full factorial design in terms of experimental runs and resources. In other words, it makes use of the fact that many experiments in full factorial design are often redundant, giving little or no new information about the system. Notation Fractional designs are expressed using the notation ''l''k − p, where ''l'' is the number of levels of each factor investigated, ''k'' is the number of factors investigated, and ''p'' describes the size of the fraction of the full factorial used. Formally, ''p'' is the number of ''generators'', assignments as to which effects or interactions are ''confounded'', ''i.e.'', ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
