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  2. Comparison of statistical packages - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_statistical...

    "Trends in Applied Econometrics Software Development 1985–2008: An Analysis of Journal of Applied Econometrics Research Articles, Software Reviews, Data and Code". Palgrave Handbook of Econometrics .

  3. SAS (software) - Wikipedia

    en.wikipedia.org/wiki/SAS_(software)

    SAS (previously "Statistical Analysis System") [1] is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, [2] and predictive analytics. SAS' analytical software is built upon artificial intelligence and utilizes machine learning ...

  4. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    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.

  5. Select (SQL) - Wikipedia

    en.wikipedia.org/wiki/Select_(SQL)

    SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.

  6. RATS (software) - Wikipedia

    en.wikipedia.org/wiki/RATS_(software)

    The following is a list of the major procedures in econometrics and time series analysis that can be implemented in RATS. All these methods can be used in order to forecast, as well as to conduct data analysis. In addition, RATS can handle cross-sectional and panel data: Linear regression, including stepwise.

  7. Functional data analysis - Wikipedia

    en.wikipedia.org/wiki/Functional_data_analysis

    Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function.

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  9. Five-number summary - Wikipedia

    en.wikipedia.org/wiki/Five-number_summary

    It helps to put the observations in ascending order: 0, 0, 1, 2, 13, 27, 61, 63. There are eight observations, so the median is the mean of the two middle numbers, (2 + 13)/2 = 7.5. Splitting the observations either side of the median gives two groups of four observations.