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  2. 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.

  3. Bayesian statistics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_statistics

    t. e. Bayesian statistics (/ ˈbeɪziən / BAY-zee-ən or / ˈbeɪʒən / BAY-zhən) [ 1 ] is a theory in the field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous ...

  4. Statistical Methods for Research Workers - Wikipedia

    en.wikipedia.org/wiki/Statistical_Methods_for...

    Ronald Fisher. Statistical Methods for Research Workers is a classic book on statistics, written by the statistician R. A. Fisher. It is considered by some [who?] to be one of the 20th century's most influential books on statistical methods, together with his The Design of Experiments (1935). It was originally published in 1925, by Oliver ...

  5. Jackknife resampling - Wikipedia

    en.wikipedia.org/wiki/Jackknife_resampling

    Jackknife resampling. In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful for bias and variance estimation. The jackknife pre-dates other common resampling methods such as the bootstrap. Given a sample of size , a jackknife estimator can be built ...

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    e. Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. [1] Recently, artificial neural networks have been able to surpass many previous approaches in ...

  7. Variational Bayesian methods - Wikipedia

    en.wikipedia.org/wiki/Variational_Bayesian_methods

    Variational Bayesian methods are a family of techniques for approximating intractable integrals arising in Bayesian inference and machine learning.They are typically used in complex statistical models consisting of observed variables (usually termed "data") as well as unknown parameters and latent variables, with various sorts of relationships among the three types of random variables, as ...

  8. Method of moments (statistics) - Wikipedia

    en.wikipedia.org/wiki/Method_of_moments_(statistics)

    Method of moments (statistics) In statistics, the method of moments is a method of estimation of population parameters. The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of ...

  9. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Qlucore Omics Explorer – interactive and visual data analysis software. RapidMiner – machine learning toolbox. Regression Analysis of Time Series (RATS) – comprehensive econometric analysis package. Rguroo Statistical Software - An online statistical software designed for teaching and analyzing data.