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Plot with random data showing heteroscedasticity: The variance of the y-values of the dots increases with increasing values of x. 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 ...
Cultural consensus theory assumes that cultural beliefs are learned and shared across people and that there is a common understanding of what the world and society are all about. [2] Since the amount of information in a culture is too large for any one individual to master, individuals know different subsets of the cultural knowledge and vary ...
Funnel plots, introduced by Light and Pillemer in 1984 [1] and discussed in detail by Matthias Egger and colleagues, [2] [3] are useful adjuncts to meta-analyses. A funnel plot is a scatterplot of treatment effect against a measure of study precision. It is used primarily as a visual aid for detecting bias or systematic 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]
Cultural analytics refers to the use of computational, visualization, and big data methods for the exploration of contemporary and historical cultures. While digital humanities research has focused on text data, cultural analytics has a particular focus on massive cultural data sets of visual material – both digitized visual artifacts and contemporary visual and interactive media.
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.
where is the grand mean, is the additive main effect of level from the first factor (i-th row in the contingency table), is the additive main effect of level from the second factor (j-th column in the contingency table) and is the non-additive interaction effect of treatment (,) for samples =,..., from both factors (cell at row i and column j ...
The two graphics illustrate sampling distributions of polygenic scores and the predictive ability of stratified sampling on polygenic risk score with increasing age. + The left panel shows how risk—(the standardized PRS on the x-axis)—can separate 'cases' (i.e., individuals with a certain disease, (red)) from the 'controls' (individuals without the disease, (blue)).