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Theodore Wilbur Anderson
Theodore Wilbur Anderson (June 5, 1918 – September 17, 2016) was an American mathematician and statistician who specialized in the analysis of multivariate data. He was born in Minneapolis, Minnesota. He was on the faculty of Columbia University from 1946 until moving to Stanford University in 1967, becoming Emeritus Professor in 1988. He served as Editor of ''Annals of Mathematical Statistics'' from 1950 to 1952. He was elected President of the Institute of Mathematical Statistics in 1962. Anderson's 1958 textbook,'' An Introduction to Multivariate Analysis'', educated a generation of theorists and applied statisticians; it was "the classic" in the area until the book by Mardia, Kent and Bibb Anderson's book emphasizes hypothesis testing via likelihood ratio tests and the properties of power functions: Admissibility, unbiasedness and monotonicity. Anderson is also known for Anderson–Darling test of whether there is evidence that a given sample of data did not arise fro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minneapolis
Minneapolis () is the largest city in Minnesota, United States, and the county seat of Hennepin County. The city is abundant in water, with thirteen lakes, wetlands, the Mississippi River, creeks and waterfalls. Minneapolis has its origins in timber and as the flour milling capital of the world. It occupies both banks of the Mississippi River and adjoins Saint Paul, the state capital of Minnesota. Prior to European settlement, the site of Minneapolis was inhabited by Dakota people. The settlement was founded along Saint Anthony Falls on a section of land north of Fort Snelling; its growth is attributed to its proximity to the fort and the falls providing power for industrial activity. , the city has an estimated 425,336 inhabitants. It is the most populous city in the state and the 46th-most-populous city in the United States. Minneapolis, Saint Paul and the surrounding area are collectively known as the Twin Cities. Minneapolis has one of the most extensive public par ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hypothesis Testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson ( ''p''-value, Pearson's chi-squared test), William Sealy Gosset ( Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher soon grew disenchanted with t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
American Academy Of Arts And Sciences
The American Academy of Arts and Sciences (abbreviation: AAA&S) is one of the oldest learned societies in the United States. It was founded in 1780 during the American Revolution by John Adams, John Hancock, James Bowdoin, Andrew Oliver, and other Founding Fathers of the United States. It is headquartered in Cambridge, Massachusetts. Membership in the academy is achieved through a thorough petition, review, and election process. The academy's quarterly journal, ''Dædalus'', is published by MIT Press on behalf of the academy. The academy also conducts multidisciplinary public policy research. History The Academy was established by the Massachusetts legislature on May 4, 1780, charted in order "to cultivate every art and science which may tend to advance the interest, honor, dignity, and happiness of a free, independent, and virtuous people." The sixty-two incorporating fellows represented varying interests and high standing in the political, professional, and commercial secto ... [...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] |
Guggenheim Fellowship
Guggenheim Fellowships are grants that have been awarded annually since by the John Simon Guggenheim Memorial Foundation to those "who have demonstrated exceptional capacity for productive scholarship or exceptional creative ability in the arts." Each year, the foundation issues awards in each of two separate competitions: * One open to citizens and permanent residents of the United States and Canada. * The other to citizens and permanent residents of Latin America and the Caribbean. The Latin America and Caribbean competition is currently suspended "while we examine the workings and efficacy of the program. The U.S. and Canadian competition is unaffected by this suspension." The performing arts are excluded, although composers, film directors, and choreographers are eligible. The fellowships are not open to students, only to "advanced professionals in mid-career" such as published authors. The fellows may spend the money as they see fit, as the purpose is to give fellows "b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Covariance Matrix
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector. Any covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the covariance of each element with itself). Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions. As an example, the variation in a collection of random points in two-dimensional space cannot be characterized fully by a single number, nor would the variances in the x and y directions contain all of the necessary information; a 2 \times 2 matrix would be necessary to fully characterize the two-dimensional variation. The covariance matrix of a random vector \mathbf is typically denoted by \operatorname_ or \Sigma. Definition Throughout this article, boldfaced unsubsc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Raghu Raj Bahadur
Raghu Raj Bahadur (30 April 1924 – 7 June 1997) was an Indian statistician considered by peers to be "one of the architects of the modern theory of mathematical statistics". Biography Bahadur was born in Delhi, India, and received his BA (1943) and MA (1945) in mathematics from St. Stephen’s College, University of Delhi . He received his doctorate from the University of North Carolina under Herbert Robbins in 1950 after which he joined University of Chicago. He worked as a research statistician at the Indian Statistical Institute in Calcutta from 1956 to 1961. He spent the remainder of his academic career in the University of Chicago. Contributions He published numerous papers and is best known for the concepts of " Bahadur efficiency" and the Bahadur–Ghosh–Kiefer representation (with J. K. Ghosh and Jack Kiefer). He also framed the Anderson–Bahadur algorithmClassification into two multivariate normal distributions with different covariance matrices (1962), ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Covariance Matrices
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector. Any covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the covariance of each element with itself). Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions. As an example, the variation in a collection of random points in two-dimensional space cannot be characterized fully by a single number, nor would the variances in the x and y directions contain all of the necessary information; a 2 \times 2 matrix would be necessary to fully characterize the two-dimensional variation. The covariance matrix of a random vector \mathbf is typically denoted by \operatorname_ or \Sigma. Definition Throughout this article, boldfaced unsubsc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Normal Distribution
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be ''k''-variate normally distributed if every linear combination of its ''k'' components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables each of which clusters around a mean value. Definitions Notation and parameterization The multivariate normal distribution of a ''k''-dimensional random vector \mathbf = (X_1,\ldots,X_k)^ can be written in the following notation: : \mathbf\ \sim\ \mathcal(\boldsymbol\mu,\, \boldsymbol\Sigma), or to make it explicitly known that ''X'' i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Journal Of The American Statistical Association
The ''Journal of the American Statistical Association (JASA)'' is the primary journal published by the American Statistical Association, the main professional body for statisticians in the United States. It is published four times a year in March, June, September and December by Taylor & Francis, Ltd on behalf of the American Statistical Association. As a statistics journal it publishes articles primarily focused on the application of statistics, statistical theory and methods in economic, social, physical, engineering, and health sciences. The journal also includes reviews of academic books which are important to the advancement of the field. It had an impact factor of 2.063 in 2010, tenth highest in the "Statistics and Probability" category of ''Journal Citation Reports''. In a 2003 survey of statisticians, the ''Journal of the American Statistical Association'' was ranked first, among all journals, for "Applications of Statistics" and second (after ''Annals of Statistics'') f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Monotonicity
In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. This concept first arose in calculus, and was later generalized to the more abstract setting of order theory. In calculus and analysis In calculus, a function f defined on a subset of the real numbers with real values is called ''monotonic'' if and only if it is either entirely non-increasing, or entirely non-decreasing. That is, as per Fig. 1, a function that increases monotonically does not exclusively have to increase, it simply must not decrease. A function is called ''monotonically increasing'' (also ''increasing'' or ''non-decreasing'') if for all x and y such that x \leq y one has f\!\left(x\right) \leq f\!\left(y\right), so f preserves the order (see Figure 1). Likewise, a function is called ''monotonically decreasing'' (also ''decreasing'' or ''non-increasing'') if, whenever x \leq y, then f\!\left(x\right) \geq f\!\left(y\ri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bias Of An Estimator
In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called ''unbiased''. In statistics, "bias" is an property of an estimator. Bias is a distinct concept from consistency: consistent estimators converge in probability to the true value of the parameter, but may be biased or unbiased; see bias versus consistency for more. All else being equal, an unbiased estimator is preferable to a biased estimator, although in practice, biased estimators (with generally small bias) are frequently used. When a biased estimator is used, bounds of the bias are calculated. A biased estimator may be used for various reasons: because an unbiased estimator does not exist without further assumptions about a population; because an estimator is difficult to compute (as in unbiased estimation of standard deviation); because a biased estimato ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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