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  2. 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 ...

  3. Descriptive statistics - Wikipedia

    en.wikipedia.org/wiki/Descriptive_statistics

    The use of descriptive and summary statistics has an extensive history and, indeed, the simple tabulation of populations and of economic data was the first way the topic of statistics appeared. More recently, a collection of summarisation techniques has been formulated under the heading of exploratory data analysis : an example of such a ...

  4. Statistica - Wikipedia

    en.wikipedia.org/wiki/STATISTICA

    Statistica is a suite of analytics software originally developed by StatSoft and acquired by Dell in March 2014. The software includes an array of data analysis, data management, data visualization, and data mining procedures; as well as a variety of predictive modeling, clustering, classification, and exploratory techniques. [2]

  5. Multidimensional analysis - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_analysis

    In statistics, econometrics and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data ...

  6. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    Prediction outside this range of the data is known as extrapolation. Performing extrapolation relies strongly on the regression assumptions. The further the extrapolation goes outside the data, the more room there is for the model to fail due to differences between the assumptions and the sample data or the true values.

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