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Everything about Pooled variance
Method for estimating variance of several different populations
In statistics, pooled variance is a method for estimating variance of several different populations when the mean of each population may be different, but one may assume that the variance of each population is the same. The numerical estimate resulting from the use of this method is also called the pooled variance. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Pooled varianceA 5-minute orientation
- Skim a recent paper: RAPID: Robust multi-pAtch masker using channel-wise Pooled varIance with two-stage patch DetectionInfluential work since 2022
- Pick up a classic book: Introduction to Probability and StatisticsThe most-reprinted book on the subject
- Read the landmark paper: Using pooled data to estimate variance components and breeding values for traits affected by social interactionsCited 23 times
- Go sideways: VarianceA closely related topic
- Go sideways: Standard deviationA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Using pooled data to estimate variance components and breeding values for traits affected by social interactions
Why do we use pooled variance analysis of variance?
Estimation of variance components and prediction of breeding values using pooled data1
The Effect of Pooled and Un-Pooled Variance Estimators on CpmWhen Using Subsamples
Heteroskedasticity Robust Panel Unit Root Testing Under Variance Breaks in Pooled Regressions
Constructing control charts for autocorrelated data using an exhaustive systematic samples pooled variance estimator
Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders
A more efficient three-arm non-inferiority test based on pooled estimators of the homogeneous variance
🆕 Influential since 2022
đź“š Books worth reading
Introduction to Probability and StatisticsJ. Susan Milton, Jesse C. Arnold · 1990
Numbers rule your worldKaiser Fung · 2010- 📕Analysis of varianceHelen Bozivich · 1956
Estimation of variance components and applicationsRao, C. Radhakrishna · 1988
Introduction to probability and statisticsJ. Susan Milton, Jesse C. Arnold · 2002
Batch effects and noise in microarray experiments, sources, and solutionsAndreas Scherer · 2009
Cointegration, causality, and forecastingR. F. Engle, Halbert White · 1999
Energy production and services in FinlandPhilip M. Parker · 2007
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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