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  2. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training set (left) and a test set (right) from the same statistical population are shown as blue points. Two predictive models are fit to the training data. Both fitted models are plotted with both the training and test sets. In the training set, the MSE of the fit shown in orange is 4 whereas the MSE for the fit shown in green is 9. In the ...

  3. Hartley's test - Wikipedia

    en.wikipedia.org/wiki/Hartley's_test

    The test involves computing the ratio of the largest group variance, max(s j 2) to the smallest group variance, min(s j 2). The resulting ratio, F max, is then compared to a critical value from a table of the sampling distribution of F max. [2] [3] If the computed ratio is less than the critical value, the groups are assumed to have similar or ...

  4. Box–Behnken design - Wikipedia

    en.wikipedia.org/wiki/Box–Behnken_design

    Each factor, or independent variable, is placed at one of three equally spaced values, usually coded as −1, 0, +1. (At least three levels are needed for the following goal.) The design should be sufficient to fit a quadratic model , that is, one containing squared terms, products of two factors, linear terms and an intercept.

  5. Multiple factor analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_factor_analysis

    MFA treats all involved tables in the same way (symmetrical analysis). It may be seen as an extension of: Principal component analysis (PCA) when variables are quantitative, Multiple correspondence analysis (MCA) when variables are qualitative, Factor analysis of mixed data (FAMD) when the active variables belong to the two types.

  6. JASP - Wikipedia

    en.wikipedia.org/wiki/JASP

    Descriptives: Explore the data with tables and plots. T-Tests: Evaluate the difference between two means. ANOVA: Evaluate the difference between multiple means. Mixed Models: Evaluate the difference between multiple means with random effects. Regression: Evaluate the association between variables. Frequencies: Analyses for count data.

  7. Spaces of test functions and distributions - Wikipedia

    en.wikipedia.org/wiki/Spaces_of_test_functions...

    In mathematical analysis, the spaces of test functions and distributions are topological vector spaces (TVSs) that are used in the definition and application of distributions. Test functions are usually infinitely differentiable complex -valued (or sometimes real -valued) functions on a non-empty open subset U ⊆ R n {\displaystyle U\subseteq ...

  8. Barnard's test - Wikipedia

    en.wikipedia.org/wiki/Barnard's_test

    Barnard’s test is used to test the independence of rows and columns in a 2 × 2 contingency table. The test assumes each response is independent. Under independence, there are three types of study designs that yield a 2 × 2 table, and Barnard's test applies to the second type.

  9. Resampling (statistics) - Wikipedia

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

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...

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