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Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of numerical methods that attempt to find approximate solutions of problems rather than the exact ones.
The Topology ToolKit is specialized for continuous data defined on manifolds of low dimension (1, 2 or 3), as typically found in scientific visualization. Cubicle is optimized for large (gigabyte-scale) grayscale image data in dimension 1, 2 or 3 using cubical complexes and discrete Morse theory.
Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...
SAS Institute (or SAS, pronounced "sass") is an American multinational developer of analytics and artificial intelligence software based in Cary, North Carolina.SAS develops and markets a suite of analytics software (also called SAS), which helps access, manage, analyze and report on data to aid in decision-making.
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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.
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