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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.
R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also
a researcher is interested in whether students who attend privte high schools have higher average SAT Scores than students in the general population. a random sample of 90 student
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
Blinding : A procedure used in clinical trials to get rid of the possible bias which might be introduced if the patient and/or the doctor knew which treatment the patient is receiv
MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo
An auditor for a government agency needs to evaluate payments for doctors' office visits paid by Medicare in a small regional town during the month of June. A total of 25,056 visit
Correlation matrix : A square, symmetric matrix with the rows and columns corresponding to the variables, in which the non diagonal elements are correlations between the pairs of t
Confounding: A procedure observed in some factorial designs in which it is impossible to differentiate between some main effects or interactions, on the basis of the particular d
Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
Normal approximation : Normal distributions which approximate other distributions; such as, a normal distribution with the mean np and variance np(1 - p) which acts as an approxima
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