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  2. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...

  3. Data validation and reconciliation - Wikipedia

    en.wikipedia.org/wiki/Data_validation_and...

    Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.

  4. Analyse-it - Wikipedia

    en.wikipedia.org/wiki/Analyse-it

    Analyse-it is a statistical analysis add-in for Microsoft Excel. Analyse-it is the successor to Astute, developed in 1992 for Excel 4 and the first statistical analysis add-in for Microsoft Excel. Analyse-it is the successor to Astute, developed in 1992 for Excel 4 and the first statistical analysis add-in for Microsoft Excel.

  5. Verification and validation - Wikipedia

    en.wikipedia.org/wiki/Verification_and_validation

    Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.

  6. Cross-validation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Cross-validation_(statistics)

    The advantage of this method (over k-fold cross validation) is that the proportion of the training/validation split is not dependent on the number of iterations (i.e., the number of partitions). The disadvantage of this method is that some observations may never be selected in the validation subsample, whereas others may be selected more than once.

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

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

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. Collation - Wikipedia

    en.wikipedia.org/wiki/Collation

    When an order has been defined in this way, a sorting algorithm can be used to put a list of any number of items into that order. The main advantage of collation is that it makes it fast and easy for a user to find an element in the list, or to confirm that it is absent from the list.

  9. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]