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Related to regressions: regression analysis, Regression test


A mathematical technique used to explain and/or predict. The general form is Y = a + bX + u, where Y is the variable that we are trying to predict; X is the variable that we are using to predict Y, a is the intercept; b is the slope, and u is the regression residual. The a and b are chosen in a way to minimize the squared sum of the residuals. The ability to fit or explain is measured by the R-square.

Regression Analysis

In statistics, the analysis of variables that are dependent on other variables. Regression analysis often uses regression equations, which show the value of a dependent variable as a function of an independent variable. For example, a regression could take the form:

y = a + bx

where y is the dependent variable and x is the independent variable. In this case, the slope is equal to b and a is the intercept. When plotted on a graph, y is determined by the value of x. Regression equations are charted as a line and are important in calculating economic data and stock prices.


(1) A statistical technique for creating a mathematical equation to explain the relationship between known variables so that the model can be used to predict other variables when one has insufficient data. Multiple regression analysis is the basis of computerized automatic valuation models (AVM) employed instead of appraisals by many mortgage lenders. (2) An appraisal principle that if properties of relatively unequal value are located near each other, the one with the lower value will depress the value of the other. (3) A withdrawal of the sea from the land due to an uplift of the land or a drop in sea level.

References in periodicals archive ?
Previous analyses of wait time to treatment within the Network for the Improvement of Addiction Treatment (NIATx) employed a conventional least-squares regression analysis and estimated rates of change in the mean of the monthly averaged outcome variables (McCarty et al.
Merkel cell carcinoma of the eyelid: review of the literature and report of patients with Merkel cell carcinoma showing spontaneous regression.
To characterize genotypic stability, the following linear regression model was also used [5, 6].
It is apparent that the monthly-energy and daily-energy regressions do not match each other for this case because different days have completely different energy use profiles.
Regression analysis involves choosing the basic form of the equation, with a number of unknown coefficients, called regression coefficients.
Construct regression models for each dependent variable
The power law regression slopes ([alpha] in equation 10) were calculated for [[eta].
In an ordinary least squares regression analysis that controlled only for demographic characteristics, the higher the sexual media diet score, the more precoital behaviors black teenagers reported at follow-up.
The APS regression analyses yielded a model pertaining to the personal teaching efficacy scale (belief that one has the skills and abilities to induce student learning) for each preservice teacher group sample.
Logistic regression analysis is one of the most frequently used statistical procedures, and is especially common in medical research (King and Ryan 2002).
This figure includes two ordinary partial regression plots of the residuals of the masculine scale and ln[SIGMA]PC[B.
The disadvantages of DEA are mostly the advantages of using regressions.