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  2. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    Although the 30 samples were all simulated under the null, one of the resulting p-values is small enough to produce a false rejection at the typical level 0.05 in the absence of correction. Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a "discovery".

  3. Univariate (statistics) - Wikipedia

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

    A numerical univariate data is discrete if the set of all possible values is finite or countably infinite. Discrete univariate data are usually associated with counting (such as the number of books read by a person). A numerical univariate data is continuous if the set of all possible values is an interval of numbers.

  4. Small multiple - Wikipedia

    en.wikipedia.org/wiki/Small_multiple

    Small multiple map series showing the trends in partisan voting margins in Utah, 1900–2012. Small multiples are a popular technique in cartographic design for multivariate mapping . As with the small multiple chart, each panel uses the same underlying two-dimensional space, but in this case that is a geographic space.

  5. Multiple correspondence analysis - Wikipedia

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

    In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space .

  6. Data set - Wikipedia

    en.wikipedia.org/wiki/Data_set

    Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936). [1]A data set (or dataset) is a collection of data.In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.

  7. Multiple factor analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_factor_analysis

    The small size and simplicity of the example allow simple validation of the rules of interpretation. But the method will be more valuable when the data set is large and complex. Other methods suitable for this type of data are available. Procrustes analysis is compared to the MFA in. [2]

  8. Rasch model - Wikipedia

    en.wikipedia.org/wiki/Rasch_model

    Figure 2: Graph showing histograms of person distribution (top) and item distribution (bottom) on a scale. For dichotomous data such as right/wrong answers, by definition, the location of an item on a scale corresponds with the person location at which there is a 0.5 probability of a correct response to the question.

  9. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. [144] Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with panel data . [ 145 ]