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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.
Using World Bank (2004) World Development Indicators; Washington: International Bank for Reconstruction & Development/ The World Bank, located in the reference section of the Learn
Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th
Quasi-experiment is a term taken in use for studies which resemble experiments but are weak on some of the characteristics, particularly that allocation of the subjects to groups
Isobologram is a diagram used to characterize the interactions among jointly administered drugs or the chemicals. The contour of the constant response (that is the isobole), which
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A name sometimes given to the type of diagram generally used in meta-analysis, in which point estimates and confidence intervals are displayed for all the studies included in the a
Half-normal plot is a plot for diagnosing the model inadequacy or revealing the presence of outliers, in which the absolute values of, for instance, the residuals from the multipl
Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi
Least significant difference test is an approach to comparing a set of means which controls the family wise error rate at some specific level, let's assume it to be α. The hypothe
Path analysis is a device for evaluating the interrelationships among the variables by analyzing their correlational structure. The relationships between the variables are man
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