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  2. Fleiss' kappa - Wikipedia

    en.wikipedia.org/wiki/Fleiss'_kappa

    It can also be applied to ordinal data (ranked data): the MiniTab online documentation [1] gives an example. However, this document notes: "When you have ordinal ratings, such as defect severity ratings on a scale of 1–5, Kendall's coefficients , which account for ordering, are usually more appropriate statistics to determine association than ...

  3. Peirce's criterion - Wikipedia

    en.wikipedia.org/wiki/Peirce's_criterion

    The following Python code returns x-squared values for a given N (first column) and n (top row) in Table 1 (m = 1) and Table 2 (m = 2) of Gould 1855. [5] Due to the Newton-method of iteration, look-up tables, such as N versus log Q (Table III in Gould, 1855) and x versus log R (Table III in Peirce, 1852 and Table IV in Gould, 1855) are no ...

  4. Contingency table - Wikipedia

    en.wikipedia.org/wiki/Contingency_table

    C suffers from the disadvantage that it does not reach a maximum of 1.0, notably the highest it can reach in a 2 × 2 table is 0.707 . It can reach values closer to 1.0 in contingency tables with more categories; for example, it can reach a maximum of 0.870 in a 4 × 4 table.

  5. Confusion matrix - Wikipedia

    en.wikipedia.org/wiki/Confusion_matrix

    In predictive analytics, a table of confusion (sometimes also called a confusion matrix) is a table with two rows and two columns that reports the number of true positives, false negatives, false positives, and true negatives. This allows more detailed analysis than simply observing the proportion of correct classifications (accuracy).

  6. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow ...

  7. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    The Nested Set model is appropriate where the tree element and one or two attributes are the only data, but is a poor choice when more complex relational data exists for the elements in the tree. Given an arbitrary starting depth for a category of 'Vehicles' and a child of 'Cars' with a child of 'Mercedes', a foreign key table relationship must ...

  8. Simple matching coefficient - Wikipedia

    en.wikipedia.org/wiki/Simple_matching_coefficient

    is the total number of attributes where A has value 0 and B has value 1, and M 10 {\displaystyle M_{10}} is the total number of attributes where A has value 1 and B has value 0. The simple matching distance (SMD) , which measures dissimilarity between sample sets, is given by 1 − SMC {\displaystyle 1-{\text{SMC}}} .

  9. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    The values 1 and 0; the values 1 and −1, often simply abbreviated by + and −; A lower-case letter with the exponent 0 or 1. If these values represent "low" and "high" settings of a treatment, then it is natural to have 1 represent "high", whether using 0 and 1 or −1 and 1. This is illustrated in the accompanying table for a 2×2 experiment.