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  2. Null (SQL) - Wikipedia

    en.wikipedia.org/wiki/Null_(SQL)

    In SQL, null or NULL is a special marker used to indicate that a data value does not exist in the database. Introduced by the creator of the relational database model, E. F. Codd , SQL null serves to fulfill the requirement that all true relational database management systems ( RDBMS ) support a representation of "missing information and ...

  3. Missing data - Wikipedia

    en.wikipedia.org/wiki/Missing_data

    Generally speaking, there are three main approaches to handle missing data: (1) Imputation—where values are filled in the place of missing data, (2) omission—where samples with invalid data are discarded from further analysis and (3) analysis—by directly applying methods unaffected by the missing values. One systematic review addressing ...

  4. Nullable type - Wikipedia

    en.wikipedia.org/wiki/Nullable_type

    Nullable types are a feature of some programming languages which allow a value to be set to the special value NULL instead of the usual possible values of the data type.In statically typed languages, a nullable type is an option type, [citation needed] while in dynamically typed languages (where values have types, but variables do not), equivalent behavior is provided by having a single null ...

  5. Imputation (statistics) - Wikipedia

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

    Because missing data can create problems for analyzing data, imputation is seen as a way to avoid pitfalls involved with listwise deletion of cases that have missing values. That is to say, when one or more values are missing for a case, most statistical packages default to discarding any case that has a missing value, which may introduce bias ...

  6. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    If the probability of obtaining a result as extreme as the one obtained, supposing that the null hypothesis were true, is lower than a pre-specified cut-off probability (for example, 5%), then the result is said to be statistically significant and the null hypothesis is rejected.

  7. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").

  8. NaN - Wikipedia

    en.wikipedia.org/wiki/NaN

    In the IEEE 754 binary interchange formats, NaNs are encoded with the exponent field filled with ones (like infinity values), and some non-zero number in the trailing significand field (to make them distinct from infinity values); this allows the definition of multiple distinct NaN values, depending on which bits are set in the trailing ...

  9. Null object pattern - Wikipedia

    en.wikipedia.org/wiki/Null_object_pattern

    In object-oriented computer programming, a null object is an object with no referenced value or with defined neutral (null) behavior.The null object design pattern, which describes the uses of such objects and their behavior (or lack thereof), was first published as "Void Value" [1] and later in the Pattern Languages of Program Design book series as "Null Object".