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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These methods can, however, be used in creating new hypotheses to ...

  3. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...

  4. Small multiple - Wikipedia

    en.wikipedia.org/wiki/Small_multiple

    Small multiple map series showing the trends in partisan voting margins in Utah, 1900–2012. Small multiples are a popular technique in cartographic design for multivariate mapping. As with the small multiple chart, each panel uses the same underlying two-dimensional space, but in this case that is a geographic space.

  5. Multidimensional scaling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_scaling

    Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a data set. MDS is used to translate distances between each pair of objects in a set into a configuration of points mapped into an abstract Cartesian space.

  6. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to ...

  7. Statistical graphics - Wikipedia

    en.wikipedia.org/wiki/Statistical_graphics

    In addition, the choice of appropriate statistical graphics can provide a convincing means of communicating the underlying message that is present in the data to others. [1] Graphical statistical methods have four objectives: [2] The exploration of the content of a data set; The use to find structure in data; Checking assumptions in statistical ...

  8. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    In many big data projects, there is no large data analysis happening, but the challenge is the extract, transform, load part of data pre-processing. [225] Big data is a buzzword and a "vague term", [226] [227] but at the same time an "obsession" [227] with entrepreneurs, consultants, scientists, and the media.

  9. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    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.