# Regression equation

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## Regression equation

An equation that describes the average relationship between a dependent variable and a set of explanatory variables.

## Regression Equation

In statistics, an equation showing 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. 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.
References in periodicals archive ?
The variables entered into the regression equation respectively included : participation in courses, technical skills, Number of pieces, distance of pieces, the pieces size.
An automated generalizer tool was built for this study with the Arc Model Builder in ArcGIS, version 10 (ESRI, Redlands, CA, USA) that allows the user to input any desired slope in the regression equation and generalize features for the entire data set within minutes.
The regression equation selected for use in the ISGM was chosen from a large number of potential options based on an iterative and adaptive process.
Management skills regression equations of managers in different countries were presented.
The result is a regression equation with four variables that describe 39.
Period-wise rates of growth by applying the regression equation in terms of linear (y = a+bt) and the semilogarithmic form (Log y + a +bt) have been portrayed in Table -8 and Table -9.
In the meanwhile, quadratic polynomial regression equation of the surface of abdomen in the cross section (x=15.
After reviewing the assumptions of regression, regression procedures between two variables basal area and the percentage of cross section surface of tree coverage cross section was performed and the relevant regression equation was obtained.
More work needs to be done to understand issues related to the shear-wave velocity distribution, variability in site geology, and conditions under which the regression equations might be transferable to other sites where geology and lithology are similar.
Most of the theoretically derived parameters in Chapters 2 and 3 were not employed in the regression equations of Chapter 4.
After statistical processing and analysis of the obtained data we have established the following types of regression equations for the dependence between the studied parameters:

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