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  2. Pooled analysis - Wikipedia

    en.wikipedia.org/wiki/Pooled_analysis

    A pooled analysis is a statistical technique for combining the results of multiple epidemiological studies. It is one of three types of literature reviews frequently used in epidemiology, along with meta-analysis and traditional narrative reviews. Pooled analyses may be either retrospective or prospective. [1]

  3. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]

  4. Object pool pattern - Wikipedia

    en.wikipedia.org/wiki/Object_pool_pattern

    The object pool design pattern is used in several places in the standard classes of the .NET Framework. One example is the .NET Framework Data Provider for SQL Server. As SQL Server database connections can be slow to create, a pool of connections is maintained. Closing a connection does not actually relinquish the link to SQL Server.

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  6. Pooled variance - Wikipedia

    en.wikipedia.org/wiki/Pooled_variance

    Pooled variance is an estimate when there is a correlation between pooled data sets or the average of the data sets is not identical. Pooled variation is less precise the more non-zero the correlation or distant the averages between data sets. The variation of data for non-overlapping data sets is:

  7. Multilevel model - Wikipedia

    en.wikipedia.org/wiki/Multilevel_model

    Another way to analyze the data using traditional statistical approaches is to aggregate individual level variables to higher-order variables and then to conduct an analysis on this higher level. The problem with this approach is that it discards all within-group information (because it takes the average of the individual level variables).

  8. Grand mean - Wikipedia

    en.wikipedia.org/wiki/Grand_mean

    The grand mean or pooled mean is the average of the means of several subsamples, as long as the subsamples have the same number of data points. [1] For example, consider several lots, each containing several items. The items from each lot are sampled for a measure of some variable and the means of the measurements from each lot are computed ...

  9. Panel analysis - Wikipedia

    en.wikipedia.org/wiki/Panel_analysis

    Panel (data) analysis is a statistical method, widely used in social science, epidemiology, and econometrics to analyze two-dimensional (typically cross sectional and longitudinal) panel data. [1] The data are usually collected over time and over the same individuals and then a regression is run over these two dimensions.