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Francis Anscombe
Francis John Anscombe (13 May 1918 – 17 October 2001) was an English statistician. Born in Hove in England, Anscombe was educated at Trinity College at Cambridge University. After serving in the Second World War, he joined Rothamsted Experimental Station for two years before returning to Cambridge as a lecturer. In experiments, Anscombe emphasized randomization in both the design and analysis phases. In the design phase, Anscombe argued that the experimenters should randomize the labels of blocks. In the analysis phase, Anscombe argued that the randomization plan should guide the analysis of data; Anscombe's approach has influenced John Nelder and R. A. Bailey in particular. He moved to Princeton University in 1956, and in the same year he was elected as a Fellow of the American Statistical Association. He became the founding chairman of the statistics department at Yale University in 1963. According to David Cox, his best-known work may be his 1961 account of for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hove
Hove is a seaside resort and one of the two main parts of the city of Brighton and Hove, along with Brighton in East Sussex, England. Originally a "small but ancient fishing village" surrounded by open farmland, it grew rapidly in the 19th century in response to the development of its eastern neighbour Brighton, and by the Victorian era it was a fully developed town with borough status. Neighbouring parishes such as Aldrington and Hangleton were annexed in the late 19th and early 20th centuries. The neighbouring urban district of Portslade was merged with Hove in 1974. In 1997, as part of local government reform, the borough merged with Brighton to form the Borough of Brighton and Hove, and this unitary authority was granted city status in 2000. Name and etymology Old spellings of Hove include Hou (Domesday Book, 1086), la Houue (1288), Huua (13th century), Houve (13th and 14th centuries), Huve (14th and 15th centuries), Hova (16th century) and Hoova (1675). The etymology ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Randomization
Randomization is the process of making something random. Randomization is not haphazard; instead, a random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. For example, a random sample of individuals from a population refers to a sample where every individual has a known probability of being sampled. This would be contrasted with nonprobability sampling where arbitrary individuals are selected. In various contexts, randomization may involve: * generating a random permutation of a sequence (such as when shuffling cards); * selecting a random sample of a population (important in statistical sampling); * allocating experimental units via random assignment to a treatment or control condition; * generating random numbers (random number generation); or * transforming a data stream (such as when using a scrambler in telecommunications). Applications Randomi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
APL (programming Language)
APL (named after the book ''A Programming Language'') is a programming language developed in the 1960s by Kenneth E. Iverson. Its central datatype is the Array data type#Multi-dimensional arrays, multidimensional array. It uses a large range of APL syntax and symbols, special graphic symbols to represent most functions and operators, leading to very concise code. It has been an important influence on the development of concept modeling, spreadsheets, functional programming, and computer math packages. It has also inspired several other programming languages. History Mathematical notation A mathematical notation for manipulating arrays was developed by Kenneth E. Iverson, starting in 1957 at Harvard University. In 1960, he began work for IBM where he developed this notation with Adin Falkoff and published it in his book ''A Programming Language'' in 1962. The preface states its premise: This notation was used inside IBM for short research reports on computer systems, such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Computing
Computational statistics, or statistical computing, is the bond between statistics and computer science. It means statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is also developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education. As in traditional statistics the goal is to transform raw data into knowledge, Wegman, Edward J. �Computational Statistics: A New Agenda for Statistical Theory and Practice.�� Journal of the Washington Academy of Sciences', vol. 78, no. 4, 1988, pp. 310–322. ''JSTOR'' but the focus lies on computer intensive statistical methods, such as cases with very large sample size and non-homogeneous data sets. The terms 'computational statistics' and 'statistical computing' are often used interchangeably, although Carlo Lauro (a former preside ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Poisson Distribution
In probability theory and statistics, the Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant mean rate and Statistical independence, independently of the time since the last event. It is named after France, French mathematician Siméon Denis Poisson (; ). The Poisson distribution can also be used for the number of events in other specified interval types such as distance, area, or volume. For instance, a call center receives an average of 180 calls per hour, 24 hours a day. The calls are independent; receiving one does not change the probability of when the next one will arrive. The number of calls received during any minute has a Poisson probability distribution with mean 3: the most likely numbers are 2 and 3 but 1 and 4 are also likely and there is a small probability of it being as low as zero and a very smal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Variance-stabilizing Transformation
In applied statistics, a variance-stabilizing transformation is a data transformation that is specifically chosen either to simplify considerations in graphical exploratory data analysis or to allow the application of simple regression-based or analysis of variance techniques. Overview The aim behind the choice of a variance-stabilizing transformation is to find a simple function ''ƒ'' to apply to values ''x'' in a data set to create new values such that the variability of the values ''y'' is not related to their mean value. For example, suppose that the values x are realizations from different Poisson distributions: i.e. the distributions each have different mean values ''μ''. Then, because for the Poisson distribution the variance is identical to the mean, the variance varies with the mean. However, if the simple variance-stabilizing transformation :y=\sqrt \, is applied, the sampling variance associated with observation will be nearly constant: see Anscombe transform for d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Regression
In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called '' simple linear regression''; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
David Cox (statistician)
Sir David Roxbee Cox (15 July 1924 – 18 January 2022) was a British statistician and educator. His wide-ranging contributions to the field of statistics included introducing logistic regression, the proportional hazards model and the Cox process, a point process named after him. He was a professor of statistics at Birkbeck College, London, Imperial College London and the University of Oxford, and served as Warden of Nuffield College, Oxford. The first recipient of the International Prize in Statistics, he also received the Guy, George Box and Copley medals, as well as a knighthood. Early life Cox was born in Birmingham on 15 July 1924. His father was a die sinker and part-owner of a jewellery shop, and they lived near the Jewellery Quarter. The aeronautical engineer Harold Roxbee Cox was a distant cousin. He attended Handsworth Grammar School, Birmingham. He received a Master of Arts in mathematics at St John's College, Cambridge, and obtained his PhD from the Universi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fellow Of The American Statistical Association
Like many other academic professional societies, the American Statistical Association (ASA) uses the title of Fellow of the American Statistical Association as its highest honorary grade of membership. The number of new fellows per year is limited to one third of one percent of the membership of the ASA. , the people that have been named as Fellows are listed below. Fellows 1914 * John Lee Coulter * Miles Menander Dawson * Frank H. Dixon * David Parks Fackler * Henry Walcott Farnam * Charles Ferris Gettemy * Franklin Henry Giddings * Henry J. Harris * Edward M. Hartwell * Joseph A. Hill * George K. Holmes * William Chamberlin Hunt * John Koren * Thomas Bassett Macaulay * S. N. D. North * Warren M. Persons * Edward B. Phelps * LeGrand Powers * William Sidney Rossiter * Charles H. Verrill * Cressy L. Wilbur * S. Herbert Wolfe * Allyn Abbott Young 1916 * Victor S. Clark * Frederick Stephen Crum * Louis Israel Dublin * Walter Sherman Gifford * James Waterman Glover * Roy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Nelder
John Ashworth Nelder (8 October 1924 – 7 August 2010) was a British statistician known for his contributions to experimental design, analysis of variance, computational statistics, and statistical theory. Contributions Nelder's work was influential in statistics. While leading research at Rothamsted Experimental Station, Nelder developed and supervised the updating of the statistical software packages GLIM and GenStat: Both packages are flexible high-level programming languages that allow statisticians to formulate linear models concisely. GLIM influenced later environments for statistical computing such as S-PLUS and R. Both GLIM and GenStat have powerful facilities for the analysis of variance for block experiments, an area where Nelder made many contributions. In statistical theory, Nelder and Wedderburn proposed the generalized linear model. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical mod ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Analysis Of Variance
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the ''t''-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means. History While the analysis of variance reached fruition in the 20th century, antecedents extend centuries into the past according to Stigler. These include hypothesis testing, the partitioning of sums of squares, experimental techniques and the additive model. Laplace was performing hypothesis testing ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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