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  2. Standardization - Wikipedia

    en.wikipedia.org/wiki/Standardization

    Standardization (American English) or standardisation (British English) is the process of implementing and developing technical standards based on the consensus of different parties that include firms, users, interest groups, standards organizations and governments. [1]

  3. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance.

  4. Normalization (statistics) - Wikipedia

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

    This is common on standardized tests. See also quantile normalization. Normalization by adding and/or multiplying by constants so values fall between 0 and 1. This is used for probability density functions, with applications in fields such as quantum mechanics in assigning probabilities to | ψ | 2.

  5. Standard score - Wikipedia

    en.wikipedia.org/wiki/Standard_score

    Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.

  6. Data definition specification - Wikipedia

    en.wikipedia.org/wiki/Data_definition_specification

    A data definition specification requires data definitions to be: Atomic – singular, describing only one concept. Commonly used and ambiguous terms should be defined. [2] While a term refers to one concept, several words may be used in a term: File – A concept identifiable with one word; File extension – A concept identifiable with more ...

  7. Why colleges are adopting standardized tests again

    www.aol.com/why-colleges-adopting-standardized...

    Standardized test scores might be the best success indicator for lower-income students. With conflicting data on standardized tests, holistic admissions have gained favor in recent years, an ...

  8. Industry standard data model - Wikipedia

    en.wikipedia.org/wiki/Industry_standard_data_model

    An industry standard data model, or simply standard data model, is a data model that is widely used in a particular industry. The use of standard data models makes the exchange of information easier and faster because it allows heterogeneous organizations to share an agreed vocabulary, semantics, format, and quality standard for data.

  9. Why Some Schools Are Rethinking Standardized Tests

    www.aol.com/why-schools-rethinking-standardized...

    The first standardized tests began at the turn of the 20th century, after the founding of the College Board. The non-profit organization still administers the SAT today.