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Acronyms that contain the term regression of y on x 

What does regression of y on x mean? This page is about the various possible meanings of the acronym, abbreviation, shorthand or slang term: regression of y on x.

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AWRR

Adaptive Weighting Reverse Regression

Miscellaneous » Unclassified

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ANLR

Adjusted Non Local Regression

Miscellaneous » Unclassified

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AWR

Advantage Weighted Regression

Miscellaneous » Unclassified

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ALR

Angular Linear Regression

Academic & Science » Mathematics

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ALR

Applied Linear Regression

Miscellaneous » Unclassified

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AR

Auto Regression

Miscellaneous » Unclassified

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ARMA

Auto Regression Moving Average

Miscellaneous » Unclassified

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APPR

Automated Profiling Performance Regression

Miscellaneous » Unclassified

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BSLR

Backward Stepwise Linear Regression

Miscellaneous » Unclassified

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BSLR

Backward Stepwise Logistic Regression

Business » Logistics

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BART

Bayesian Additive Regression Trees

Miscellaneous » Unclassified

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BLRM

Bayesian LogisOc Regression Model

Miscellaneous » Unclassified

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BLR

Bayesian Logistic Regression

Business » Logistics

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BLRM

Bayesian Logistic Regression Method

Business » Logistics

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BLRM

Bayesian logistic regression model

Business » Logistics

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BLSR

Between Lives Soul Regression

Miscellaneous » Unclassified

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CVR

Canonical Variate Regression

Miscellaneous » Unclassified

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CRS

Caudal Regression Syndrome

Medical » British Medicine

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CLRM

Classical Linear Regression

Miscellaneous » Unclassified

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CLRM

Classical Linear Regression Model

Miscellaneous » Unclassified

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CART

Classifcation And Regression Trees

Miscellaneous » Unclassified

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CART

Classification And Regression Tree

Computing » General Computing

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CART

Classification And Regression Trees

Computing » IT

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CART

Classification and Regression Trees

Miscellaneous » Unclassified

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CRDW

Cointegrating Regression Durbin Watson

Miscellaneous » Unclassified

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What does regression of y on x mean?

regression equation, regression of y on x(noun)
the equation representing the relation between selected values of one variable (x) and observed values of the other (y); it permits the prediction of the most probable values of y

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