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  2. Homogeneity and heterogeneity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Homogeneity_and...

    In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.

  3. Spatial heterogeneity - Wikipedia

    en.wikipedia.org/wiki/Spatial_heterogeneity

    Spatial heterogeneity is a property generally ascribed to a landscape or to a population. It refers to the uneven distribution of various concentrations of each species within an area.

  4. Spatial analysis - Wikipedia

    en.wikipedia.org/wiki/Spatial_analysis

    The Modified Temporal Unit Problem (MTUP) is a source of statistical bias that occurs in time series and spatial analysis when using temporal data that has been aggregated into temporal units. [ 7 ] [ 8 ] In such cases, choosing a temporal unit (e.g., days, months, years) can affect the analysis results and lead to inconsistencies or errors in ...

  5. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.

  6. Study heterogeneity - Wikipedia

    en.wikipedia.org/wiki/Study_heterogeneity

    The heterogeneity variance is commonly denoted by τ², or the standard deviation (its square root) by τ. Heterogeneity is probably most readily interpretable in terms of τ, as this is the heterogeneity distribution's scale parameter, which is measured in the same units as the overall effect itself. [18]

  7. Cross-sectional data - Wikipedia

    en.wikipedia.org/wiki/Cross-sectional_data

    In statistics and econometrics, cross-sectional data is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at a single point or period of time. Analysis of cross-sectional data usually consists of comparing the differences among selected subjects, typically with no regard to differences in time.

  8. Federated learning - Wikipedia

    en.wikipedia.org/wiki/Federated_learning

    Heterogeneity between the different local datasets: each node may have some bias with respect to the general population, and the size of the datasets may vary significantly; [6] Temporal heterogeneity: each local dataset's distribution may vary with time; Interoperability of each node's dataset is a prerequisite;

  9. Spatial ecology - Wikipedia

    en.wikipedia.org/wiki/Spatial_ecology

    Spatial ecology studies the ultimate distributional or spatial unit occupied by a species.In a particular habitat shared by several species, each of the species is usually confined to its own microhabitat or spatial niche because two species in the same general territory cannot usually occupy the same ecological niche for any significant length of time.