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

explanatory variables (regressor or independent variable). A model with exactly one explanatory variable is a simple linear regression; a model with two or...

MANCOVA, ordinary linear regression, t-test and F-test. The general linear model is a generalization of multiple linear regression to the case of more...

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...

Quantile regression is an extension of linear regression used when the conditions of linear regression are not met. One advantage of quantile regression relative...

{\displaystyle y} -intercept The least squares regression line is a method in simple linear regression for modeling the linear relationship between two variables...

of the simplicity of linear least squares regression with the flexibility of nonlinear regression. It does this by fitting simple models to localized subsets...

In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship...

In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable...

In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination...

an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimates the...

non-linear models (e.g., nonparametric regression). Regression analysis is primarily used for two conceptually distinct purposes. First, regression analysis...

from the linear regression to the result from the t-test. From the t-test, the difference between the group means is 6-2=4. From the regression, the slope...

sometimes equivalent. One class of such cases includes that of simple linear regression where r2 is used instead of R2. When only an intercept is included...

generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model...

Nonlinear least squares Regularized least squares Simple linear regression Partial least squares regression Linear function Weisstein, Eric W. "Normal Equation"...

In statistics, regression toward the mean (also called regression to the mean, reversion to the mean, and reversion to mediocrity) is the phenomenon where...

Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes...

heteroscedastic errors Simple linear regression, the simplest type of regression, involving only one explanatory variable General linear model for multivariate...

(SSR :the sum of squares due to regression or explained sum of squares), is generally true in simple linear regression: ∑ i = 1 n ( y i − y ¯ ) 2 = ∑ i...

regression coefficient relating the y t {\displaystyle y_{t}} ′s to the actually observed x t {\displaystyle x_{t}} ′s, in a simple linear regression...

to compute than the simple linear regression. Most statistical software packages used in clinical chemistry offer Deming regression. The model was originally...

In statistics, binomial regression is a regression analysis technique in which the response (often referred to as Y) has a binomial distribution: it is...

Segmented linear regression is segmented regression whereby the relations in the intervals are obtained by linear regression. Segmented linear regression with...

Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables...

column vector of ones. This section gives an example of simple linear regression—that is, regression with only a single explanatory variable—with seven observations...

method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs...

problems involving multivariate data, for example simple linear regression and multiple regression, are not usually considered to be special cases of...

Linear regression Simple linear regression Logistic regression Nonlinear regression Nonparametric regression Robust regression Stepwise regression Regression...

used for estimating the unknown regression coefficients in a standard linear regression model. In PCR, instead of regressing the dependent variable on the...