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  2. Categorical distribution - Wikipedia

    en.wikipedia.org/wiki/Categorical_distribution

    function draw_categorical(n) // where n is the number of samples to draw from the categorical distribution r = 1 s = 0 for i from 1 to k // where k is the number of categories v = draw from a binomial(n, p[i] / r) distribution // where p[i] is the probability of category i for j from 1 to v z[s++] = i // where z is an array in which the results ...

  3. List of analyses of categorical data - Wikipedia

    en.wikipedia.org/wiki/List_of_analyses_of...

    Categorical distribution, general model; Chi-squared test; Cochran–Armitage test for trend; Cochran–Mantel–Haenszel statistics; Correspondence analysis; Cronbach's alpha; Diagnostic odds ratio; G-test; Generalized estimating equations; Generalized linear models; Krichevsky–Trofimov estimator; Kuder–Richardson Formula 20; Linear ...

  4. Fisher's exact test - Wikipedia

    en.wikipedia.org/wiki/Fisher's_exact_test

    The test is useful for categorical data that result from classifying objects in two different ways; it is used to examine the significance of the association (contingency) between the two kinds of classification. So in Fisher's original example, one criterion of classification could be whether milk or tea was put in the cup first; the other ...

  5. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    Pearson's chi-squared test or Pearson's test is a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance. It is the most widely used of many chi-squared tests (e.g., Yates , likelihood ratio , portmanteau test in time series , etc.) – statistical ...

  6. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the counterpart of principal component analysis for categorical data. [citation needed] MCA can be viewed as an extension of simple correspondence analysis (CA) in that it is applicable to a large set of categorical variables.

  7. Correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Correspondence_analysis

    Correspondence analysis (CA) is a multivariate statistical technique proposed [1] by Herman Otto Hartley (Hirschfeld) [2] and later developed by Jean-Paul Benzécri. [3] It is conceptually similar to principal component analysis, but applies to categorical rather than continuous data. In a similar manner to principal component analysis, it ...

  8. Categorical variable - Wikipedia

    en.wikipedia.org/wiki/Categorical_variable

    Categorical data is the statistical data type consisting of categorical variables or of data that has been converted into that form, for example as grouped data. More specifically, categorical data may derive from observations made of qualitative data that are summarised as counts or cross tabulations , or from observations of quantitative data ...

  9. Thomas H. Leonard - Wikipedia

    en.wikipedia.org/wiki/Thomas_H._Leonard

    Leonard's books include A Course in Categorical Data Analysis [7] and Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers, the latter co-authored with his former doctoral student, John S. J. Hsu, [8] [9] At the University of Edinburgh, Leonard collaborated with Ian Main, Orestis Papasouliotis and others on ...