• residuals
  • The chi squared test requires known standard deviations which are seldom available, and failed tests give no indication of how to improve the model An attempt to predict the residuals m(, ) with the operating conditions c using linear regression will show if the residuals can be predicted. (wikipedia.org)
  • MINITAB
  • Below are MINITAB results from a regression using Y = mean student evaluation of the professor and X = class size for 364 business school classes taught during the 2002-2003 academic year. (brainmass.com)
  • assumptions
  • Since the true form of the data-generating process is generally not known, regression analysis often depends to some extent on making assumptions about this process. (wikipedia.org)
  • Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. (wikipedia.org)
  • models
  • Overfitting is more likely to be a serious concern when there is little theory available to guide the analysis, in part because then there tend to be a large number of models to select from. (wikipedia.org)
  • Variable
  • Regression With a Qualitative Dependent Variable. (indigo.ca)
  • In seemingly unrelated regression (SUR), each response variable is a function of a subset of the exogenous series, but not of any endogenous variable. (mathworks.com)
  • A related but distinct approach is necessary condition analysis (NCA), which estimates the maximum (rather than average) value of the dependent variable for a given value of the independent variable (ceiling line rather than central line) in order to identify what value of the independent variable is necessary but not sufficient for a given value of the dependent variable. (wikipedia.org)
  • statistics
  • Many technical programs also will have regression analysis testing available, if you're seeking college credit via the AP statistics exam. (regressionanalysis.org)
  • In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest-posttest design that elicits the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. (wikipedia.org)
  • phenomenon
  • The term "regression" was coined by Francis Galton in the nineteenth century to describe a biological phenomenon. (wikipedia.org)
  • The phenomenon was that the heights of descendants of tall ancestors tend to regress down towards a normal average (a phenomenon also known as regression toward the mean). (wikipedia.org)
  • mean
  • It works on similar principles as the Working-Hotelling procedure for estimating mean responses in regression, which applies to the set of all possible factor levels. (wikipedia.org)