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High-dimensional data: This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21st century\ such data sets are collected in number of areas, such as, text/web data mining and bioinformatics. The job of extracting meaningful statistical and biological information from such data sets present many challenges for which a number of recent methodological developments, for instance, sure screening methods, lasso, and Dantzig selector, might be quite helpful.
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud
Conjoint analysis : The method used basically in market research which is similar in many respects to the various dimensional scaling. The method attempts to assign values to the l
O. J. Simpson paradox is a term coming from the claim made by the defence lawyer in murder trial of O. J. Simpson. The lawyer acknowledged that the statistics demonstrate that onl
Minimization is the method or technique for allocating patients to the treatments in clinical trials which is usually the acceptable alternative to random allocation. The procedur
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
Software which started out as the spreadsheet targeting at manipulating the tables of number for financial analysis, which has now developed into a more flexible package for workin
The Null Hypothesis - H0: There is no autocorrelation The Alternative Hypothesis - H1: There is at least first order autocorrelation Rejection Criteria: Reject H0 if LBQ1 >
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
wat iz z difference b/n logistic regression and multiple regression analysis /
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