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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.
The studies conducted in the pharmaceutical industry to calculate the degradation of the new drug product or an old drug formulated or packaged in the new manner. The main study ob
Conjugate prior : The distribution for samples from the particular probability distribution such that the posterior distribution at each stage of the sampling is of the identical f
The procedure for clustering variables in the multivariate data, which forms the clusters by performing one or other of the below written three operations: * combining two varia
Balanced incomplete block design : A design in which all the treatments are not used in all blocks. Such designs have the below stated properties: * each block comprises the
sales per day for a product are as follows: x= 10, 11, 12, 13 (p)= 0.2, 0.4, 0.3, 0.1 obtain mean and variance of daily sale. if the profit is described by the following equation p
Multidimensional scaling (MDS) is a generic term for a class of techniques or methods which attempt to construct a low-dimensional geometrical representation of the proximity matr
Higher criticism is a multiple-comparison test concept arising from the situation where there are number of independent tests of significance and interest lies in the rejecting jo
1) Has smartphones affected the consumer behavior? If so How ? And how is it going to change in future? 2) Forecasting of Mobile market (Time series analysis) 3) Comparison of fou
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
Multivariate data is the data for which each observation consists of the values for more than one random variable. For instance, measurements on the blood pressure, temperature an
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