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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.
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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.
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(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.

The Complete Real Estate Encyclopedia by Denise L. Evans, JD & O. William Evans, JD. Copyright © 2007 by The McGraw-Hill Companies, Inc.
References in periodicals archive ?
Keywords: Factor scores, Multiple linear regression, Multicollinearity, Savak Akkaraman lambs.
In the regression analysis, it is desirable to determine the function f, so that [epsilon] is a variable with the mean of zero and the minimum dispersion.
Sampling.--For the calculation of the regressions. 189 spiders (creation dataset) were sampled during five collection events in the surroundings of Karlsruhe, Baden-Wiirttemberg, Germany between 12 April and 9 May 2016.
Key words: Construction site, Fine inert waste material, Suspended particulate matter, Physico-chemical characterization, Estimation, Statistical regression.
Summary: Regression is one of the favorite tools in applied statistics.
Efe (2010).Use of cubic spline regressions in modeling dairy cattle lactation curves.KSU.
The regression is one of the most used tools in establishing the relationship between a response and an explanatory variable in applied statistics.
Patient wait times may have unequal variation due to complex interactions between variables or unobserved exogenous noises that are not accounted for in the regression model.
However, these factors become statistically much less significant on a monthly time-scale, as indicated by the high [R.sup.2] values exhibited by the monthly energy-vs.-OAT regressions. This paper's focus is on the validity of monthly energy use data since monthly energy is what most buildings are billed on.
The previously demonstrated osteochondroma on the lateral aspect of the distal femur was no longer visible, confirming its spontaneous regression.{Figure 1}{Figure 2}
In the nine studies considered high quality, patients with regression had a 52% lower likelihood of having a positive sentinel lymph node, while those enrolled in the five studies considered low quality had a 27% lower likelihood of having a positive sentinel lymph node.