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the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables...

In statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample...

{\displaystyle I} is the symbol used for electric current.) Regression intercept Weisstein, Eric W. "y-Intercept". MathWorld--A Wolfram Web Resource. Retrieved 2010-09-22...

especially in the case of a simple linear regression, in which there is a single regressor on the right side of the regression equation. The OLS estimator is consistent...

called regressors, predictors, covariates, explanatory variables or features). The most common form of regression analysis is linear regression, in which...

combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimates the parameters of a logistic model...

such cases includes that of simple linear regression where r2 is used instead of R2. When only an intercept is included, then r2 is simply the square...

distinction is most important in regression analysis, where the concepts are sometimes called the regression errors and regression residuals and where they lead...

Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable...

adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. It is a non-parametric regression technique...

multilevel regression with poststratification model involves the following pair of steps: MRP step 1 (multilevel regression): The multilevel regression model...

general regression model with n observations and k explanators, the first of which is a constant unit vector whose coefficient is the regression intercept, is...

data-sources; however the regression procedure takes no account for possible errors in estimating this ratio. The Deming regression is only slightly more...

In statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than...

general regression model with n observations and k explanators, the first of which is a constant unit vector whose coefficient is the regression intercept, is...

robust statistics, repeated median regression, also known as the repeated median estimator, is a robust linear regression algorithm. The estimator has a breakdown...

has a different regression model—with its own intercept and slope. Because groups are sampled, the model assumes that the intercepts and slopes are also...

regression analysis, are acceptable as descriptions of the data. The validation process can involve analyzing the goodness of fit of the regression,...

Then a regression of z {\displaystyle z} on y {\displaystyle y} and x {\displaystyle x} will yield an R {\displaystyle R} of zero, while a regression of y...

unusual patterns). . Partial regression plots are related to, but distinct from, partial residual plots. Partial regression plots are most commonly used...