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R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
R was originally developed by Bell Laboratories (Currently known as Lucent Technologies) by John Chambers. Since R is largely written in C language, users can use C or C++ commands to manipulate R-objects directly. Also, R runs on most UNIX platforms. R is currently part of the Free Software Foundation GNU project.
RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
Mathematical statistics is the application of probability theory and other mathematical concepts to statistics, as opposed to techniques for collecting statistical data. [1] Specific mathematical techniques that are commonly used in statistics include mathematical analysis , linear algebra , stochastic analysis , differential equations , and ...
Though computational statistics is widely used today, it actually has a relatively short history of acceptance in the statistics community. For the most part, the founders of the field of statistics relied on mathematics and asymptotic approximations in the development of computational statistical methodology.
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Low-level mathematical libraries intended for use within other programming languages: GMP, the GNU Multi-Precision Library for high-performant arbitrary precision arithmetic. Class Library for Numbers, a high-level C++ library for arbitrary precision arithmetic. AMD Core Math Library, a software development library released by AMD; Boost.Math
Misuse of statistics can be both inadvertent and intentional, and the book How to Lie with Statistics, [74] by Darrell Huff, outlines a range of considerations. In an attempt to shed light on the use and misuse of statistics, reviews of statistical techniques used in particular fields are conducted (e.g. Warne, Lazo, Ramos, and Ritter (2012)). [75]