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  "title": "Computational statistics",
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  "lead": "of the London School of Economics in 1964 Computational statistics, or statistical computing, is the study which is the intersection of statistics and computer science, and refers to the 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 fast developing. The view that the broader concept of computing must be taught as part of general statistical education is gaining momentum. As in traditional statistics the goal is to transform raw data into knowledge, 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 president of the International Association for Statistical Computing) proposed making a distinction, defining 'statistical computing' as \"the application of computer science to statistics\", and 'computational statistics' as \"aiming at the design of algorithm for implementing statistical methods on computers, including the ones unthinkable before the computer age (e.g. bootstrap, simulation), as well as to cope with analytically intractable problems\" [sic].…",
  "body": "of the London School of Economics in 1964]] Computational statistics, or statistical computing, is the study which is the intersection of statistics and computer science, and refers to the 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 fast developing. The view that the broader concept of computing must be taught as part of general statistical education is gaining momentum. As in traditional statistics the goal is to transform raw data into knowledge, 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 president of the International Association for Statistical Computing) proposed making a distinction, defining 'statistical computing' as \"the application of computer science to statistics\", and 'computational statistics' as \"aiming at the design of algorithm for implementing statistical methods on computers, including the ones unthinkable before the computer age (e.g. bootstrap, simulation), as well as to cope with analytically intractable problems\" [sic]. The term 'Computational statistics' may also be used to refer to computationally intensive statistical methods including resampling methods, Markov chain Monte Carlo methods, local regression, kernel density estimation, artificial neural networks and generalized additive models. ==Computational statistics journals== Communications in Statistics - Simulation and Computation Computational Statistics Computational Statistics & Data Analysis Journal of Computational and Graphical Statistics Journal of Statistical Computation and Simulation Journal of Statistical Software The R Journal The Stata Journal Statistics and Computing Wiley Interdisciplinary Reviews: Computational Statistics ==Associations== International Association for Statistical Computing ==See also== Algorithms for statistical classification Data science Statistical methods in artificial intelligence List of statistical algorithms List of statistical packages Machine learning ==References== ==Further reading== ===Articles=== ===Books=== ==External links== ===Associations=== International Association for Statistical Computing Statistical Computing section of the American Statistical Association ===Journals=== Computational Statistics & Data Analysis Journal of Computational & Graphical Statistics Statistics and Computing",
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