Regression analysis
Origin: Lat. regressĭo, -ōnis, Gr. ἀνάλυσις
In regression analysis, the subject under study is how the value of a "dependent variable" changes as the values of one or more "independent variables" change. Regression equations defining such changes can be linear and involve a few independent variables or be nonlinear or polynomial and involve many variables. Regression equations can be written for time series, or they may be "cross-sectional", that is, written to represent, the relationships among independent variables at any point in time. Sometimes the dependent variable of one equation is used as an independent variable in another equation. In this way "simultaneous" equations are built to describe the operation of complex systems in econometrics.
Spanish: Análisis de regresión
Sources and references
- Gordon, Theodore J. and Jerome C. Glenn .”Integration, comparisons and frontiers of FR Methods“,Futures Research Methodology V.3 The Millennium Projectcited 18 times
- The Futures Group “Statistical modeling of the series of time in simulation”view
- William H. Kruskal and Judith M. Tanur, "Linear Hypotheses," International Encyclopedia of Statistics”view
- Evan J. Williams, "I. Regression,"view
- Lindley, D.V. "Regression and correlation analysis,"view
- Birkes, David and Dodge, Y. “Alternative Methods of Regression”view
Term connections
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