Multi co linearity, Advanced Statistics

Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the regression coefficients impossible. Including the sum of explanatory variables in the regression analysis would, for instance, lead to this problem. Estimated multi co linearity can also cause problems while estimating regression coefficients. In particular if multiple correlations for the regression of the particular explanatory variable on the others is high, then the variance of corresponding estimated regression coefficient will also be quite high.

Posted Date: 7/30/2012 4:03:01 AM | Location : United States







Related Discussions:- Multi co linearity, Assignment Help, Ask Question on Multi co linearity, Get Answer, Expert's Help, Multi co linearity Discussions

Write discussion on Multi co linearity
Your posts are moderated
Related Questions
Prospective study : The studies in which individuals are followed-up over the period of time. A general example of this type of investigation is where the samples of individuals ar

Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of

Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the

Case series : It is the series of reports on the condition of the individual patients made by treating physician. Such reports might be helpful and informative for the rare disease

what are tests for residual with nonconstant variance in regression diagnostic checking?

The plot of the number of cases of the disease against the time period. A large and sudden increase corresponds to an epidemic. The example of this is shown in the figure drawn bel

Different approaches to the study of early indian history

Residual plots are the plots of some type of residual which might be helpful in assessing the assumption made by the fitted model. In regression analysis there are various method

The variables resulting from the recoding categorical variables with more than two categories into the sequence of binary variables. Marital status, for instance, if originally lab

Length-biased data is a data which arise when the probability that an item is sampled is proportional to its own length. A main example of this situation occurs in the renewal the