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Linear regression |
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Definition of Linear regressionLinear regressionA statistical technique for fitting a straight line to a set of data points.
Related Terms:Simple linear regressionA regression analysis between only two variables, one dependent and the other explanatory. First-pass regressionA time series regression to estimate the betas of securities portfolios. least squares regression analysisa statistical technique that investigates the association between dependent and independent variables; it determines the line of "best fit" for a set of observations by minimizing the sum of the squares Linear programmingTechnique for finding the maximum value of some equation subject to stated linear constraints. linear programminga method of mathematical programming used to solve a problem that involves an objective function and multiple limiting factors or constraints long-term variable cost a cost that was traditionally viewed as a fixed cost Log-linear least-squares methodA statistical technique for fitting a curve to a set of data points. One of the Multiple regressionThe estimated relationship between a dependent variable and more than one explanatory variable. multiple regressiona statistical technique that uses two or Regression analysisA statistical technique that can be used to estimate relationships between variables. Regression analysisStatistical analysis techniques that quantify the Regression equationAn equation that describes the average relationship between a dependent variable and a regression lineany line that goes through the means (or averages) of the set of observations for an independent variable and its dependent variables; mathematically, there is a line of “best fit,” which is the least squares regression line Regression toward the meanThe tendency for subsequent observations of a random variable to be closer to its mean. Second pass regressionA cross-sectional regression of portfolio returns on betas. The estimated slope is the Simple linear trend modelAn extrapolative statistical model that asserts that earnings have a base level and simple regressiona statistical technique that uses only one independent variable to predict a dependent variable R squared (R^2)Square of the correlation coefficient proportion of the variability explained by the linear
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