* Regression analysis – techniques for analyzing the relationships between several variables in the data

Regression testing can be used to test a system efficiently by systematically selecting the appropriate minimum set of tests needed to adequately cover a particular change.

Regression testing can be used not only for testing the correctness of a program, but often also for tracking the quality of its output.

Regression tests can be broadly categorized as functional tests or unit tests.

Regression analysis producing statistically significant negative relationships indicates that two individuals can be less genetically alike than two random ones on average ( Hamilton 1970, Nature & Grafen 1985 Oxford Surveys in Evolutionary Biology ).

Regression towards the mean can be defined for any bivariate distribution with identical marginal distributions.

* Regression analysis includes a large group of methods that can be used to predict future values of a variable using information about other variables.

There are also programs specifically written to do curve fitting ; they can be found in the lists of statistical and numerical analysis programs as well as in: Category: Regression and curve fitting software.

* Regression tree analysis is when the predicted outcome can be considered a real number ( e. g. the price of a house, or a patient ’ s length of stay in a hospital ).

* Regression of Weakly Correlated Data — How linear regression mistakes can appear when Y-range is much smaller than X-range

* R: The function for fitting a generalized linear model in R is glm (), and can be used for Poisson Regression

Regression to the mean in sports performance may be the reason for the “ Sports Illustrated Cover Jinx ” and the “ Madden Curse ”.

Regression toward the mean simply says that, following an extreme random event, the next random event is likely to be less extreme.

Regression analysis estimates what the average firm should be able to achieve.

Regression methods continue to be an area of active research.

* Regression test-to be performed on an existing operational product, to verify that existing functionality didn't get broken when other aspects of the environment are changed ( e. g., upgrading the platform on which an existing application runs ).

STATISTICA is customizable and may be used to call external code modules, including R. This collection of data mining and machine learning algorithms includes: Support Vector Machines, EM and k-Means Clustering, Classification & Regression Trees, Generalized Additive Models, Independent Component Analysis, Stochastic Gradient Boosted Trees, Ensembles of Neural Networks, Automatic Feature Selection, MARSplines, CHAID Trees, Nearest Neighbor Methods, Association Rules, and Random Forests.

Regression is first used to fit more

* Robust statistics-Data sets used in Robust Regression and Outlier Detection ( Rousseeuw and Leroy, 1986 ).

The term Classification And Regression Tree ( CART ) analysis is an umbrella term used to refer to both of the above procedures, first introduced by Breiman et al.

Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning.

Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships.

Hedonic Regression methods are used to estimate these price differentials.

In statistics, the explained sum of squares ( ESS ), alternatively known as the Model Sum of Squares or Sum of Squares due to Regression, is a quantity used in describing how well a model, often a regression model, represents the data being modelled.

Regression dilution arises if we are interested in the relationship between y and x, but estimate the relationship between y and w. Because w is measured with variability, the gradient of a regression line of y on w is less than the regression line of y on x.

Regression is often useful.

* Regression ( economics ), Ludwig von Mises ' theorem that tries to explain why money is demanded in its own right

Regression testing is any type of software testing that seeks to uncover new software bugs, or regressions, in existing functional and non-functional areas of a system after changes, such as enhancements, patches or configuration changes, have been made to them.

Regression testing is an integral part of the extreme programming software development method.

Regression is the situation in which a coastline moves in the direction of the sea.

Regression toward the mean is a significant consideration in the design of experiments.

Regression backwards to the safety of the womb is a unique schizoid phenomenon and represents the most intense form of schizoid defensive withdrawal in an effort to find safety and to avoid destruction by external reality.

Regression is most often manifested after exposure to prolonged changes in the quality and intensity of environmental and / or immunological stimuli.

Table 7. 7 in the book titled, " The Results of the Regression Analysis in which Real GDP Per Capita 1998 is Used as The Dependent Variable and National IQ is Used as the Independent Variable for 81 countries ".

Regression analysis on categorical outcomes is accomplished through multinomial logistic regression, multinomial probit or a related type of discrete choice model.

The name is an acronym for Gnu Regression, Econometrics and Time-series Library.

Regression analysis on predicted outcomes that are binary variables is accomplished through logistic regression, probit regression or a related type of discrete choice model.

Regression of credit usually occurs when a student has completed an upper division course in a subject, and a lower leveled or lower division CLEP exam in the same or similar subject is attempted.

Regression dilution is a statistical phenomenon also known as " attenuation ".

Recall that linear regression is not symmetric: the line of best fit for predicting y from x ( the usual linear regression ) is not the same as the line of best fit for predicting x from y ( see, for example, Draper & Smith, " Applied Regression Analysis "; page 5 of the 1966 edition ).

* Regression testing – BlueJ supports regression testing via an integration of JUnit.