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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.
Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th
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
Chapter 7 2. Describe the distribution of sample means (shape, expected value, and standard error) for samples of n =36 selected from a population with a mean of µ = 100 and a sta
Opreation research phase
Latin square is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment ef
Mixture experiment is an experiment in which the two or more ingredients are blended together to form an end product. The measurements are taken on the several blends of the ingre
Contour plot : A topographical map drawn from data comprising observations on the three variables. One variable is represented on horizontal axis and the second variable is represe
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Hazard plotting is based on the hazard function of a distribution, this procedure gives estimates of distribution parameters, the proportion of units failing by the given time per
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
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