Outline of regression analysis

In statistics, regression analysis includes any technique for learning about the relationship between one or more dependent variables Y and one or more independent variables X.

The following outline is an overview and guide to the variety of topics included within the subject of regression analysis.

General regression analysis concepts

Overview articles Regression analysis Linear regression Non-statistical articles related to regression Least squares Linear least squares (mathematics) Non-linear least squares Least absolute deviations Curve fitting Smoothing Cross-sectional study Basic statistical ideas related to regression Conditional expectation Correlation Correlation coefficient Mean square error Residual sum of squares Explained sum of squares Total sum of squares Visualization Scatterplot Linear regression based on least squares General linear model Ordinary least squares Generalized least squares Simple linear regression Trend estimation Ridge regression Polynomial regression Segmented regression Nonlinear regression Generalized linear models Generalized linear models Logistic regression Ordered logit Probit model Ordered probit Poisson regression Maximum likelihood Cochrane–Orcutt estimation Computation Numerical methods for linear least squares Inference for regression models F-test t-test Lack-of-fit sum of squares Confidence band Coefficient of determination Multiple correlation Scheffé's method Challenges to regression modeling Autocorrelation Cointegration Multicollinearity Homoscedasticity and heteroscedasticity Lack of fit Non-normality of errors Outliers

Diagnostics for regression models Regression model validation Studentized residual Cook's distance Variance inflation factor DFFITS Partial residual plot Partial regression plot Leverage Durbin–Watson statistic Formal aids to model selection Model selection Mallows' Cp Akaike information criterion Bayesian information criterion Hannan–Quinn information criterion Cross validation Robust regression Robust regression Terminology Linear model — relates to meaning of "linear" Dependent and independent variables Errors and residuals in statistics Hat matrix Trend stationary Cross-sectional data Time series Methods for dependent data Mixed model Random effects model Hierarchical linear models Nonparametric regression Nonparametric regression Isotonic regression Semiparametric regression Semiparametric regression Local regression Other forms of regression Total least squares regression Deming regression Errors-in-variables model Instrumental variables regression Quantile regression Generalized additive model Autoregressive model Moving average model Autoregressive moving average model Autoregressive integrated moving average Autoregressive conditional heteroskedasticity

See also

• Prediction
• Design of experiments
• Data transformation
• Box–Cox transformation
• Machine learning
• Analysis of variance
• Causal inference