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  2. Ordinal data - Wikipedia

    en.wikipedia.org/wiki/Ordinal_data

    Ordinal data is a categorical, statistical data type where the variables have natural, ordered categories and the distances between the categories are not known. [ 1 ] : 2 These data exist on an ordinal scale , one of four levels of measurement described by S. S. Stevens in 1946.

  3. Ordinal regression - Wikipedia

    en.wikipedia.org/wiki/Ordinal_regression

    In statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant.

  4. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1] The choice of the test depends on many properties of the research question. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use. [3] [4] [5]

  5. Order statistic - Wikipedia

    en.wikipedia.org/wiki/Order_statistic

    A similar important statistic in exploratory data analysis that is simply related to the order statistics is the sample interquartile range. The sample median may or may not be an order statistic, since there is a single middle value only when the number n of observations is odd.

  6. Kendall rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Kendall_rank_correlation...

    In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek letter τ, tau), is a statistic used to measure the ordinal association between two measured quantities. A τ test is a non-parametric hypothesis test for statistical dependence

  7. Statistical data type - Wikipedia

    en.wikipedia.org/wiki/Statistical_data_type

    The concept of data type is similar to the concept of level of measurement, but more specific. For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale).

  8. Level of measurement - Wikipedia

    en.wikipedia.org/wiki/Level_of_measurement

    Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio.

  9. Somers' D - Wikipedia

    en.wikipedia.org/wiki/Somers'_D

    In statistics, Somers’ D, sometimes incorrectly referred to as Somer’s D, is a measure of ordinal association between two possibly dependent random variables X and Y. Somers’ D takes values between − 1 {\displaystyle -1} when all pairs of the variables disagree and 1 {\displaystyle 1} when all pairs of the variables agree.