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Individual differences scaling is a form of multidimensional scaling applicable to the data comprising of a number of proximity matrices from the different sources that is different subjects. The method permits for individual differences in the perception of the stimuli by deriving weights for each subject which can be used to stretch or shrink dimensions of the recovered geometrical solution.
The rapid development or growth of the disease in a community or region. Statistical thinking has made very much significant contributions to the understanding of such type of phen
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
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
A mixture of benzene, toluene, and xylene enters a two-stage distillation process where some of the componentsare recovered. The distillation process operates at steady-state condi
The more effective display than a number of other methods or techniques, for instance, pie charts and bar charts, for displaying the quantitative data which are labeled. An instanc
Mortality odds ratio is the ratio equivalent to the odds ratio used in case-control studies where the equivalent of the cases are deaths from the cause of interest and the equival
Law of likelihood : Within framework of the statistical model, a particular set of data supports one statistical hypothesis or assumption better than another if the likelihood of t
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
The type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatm
Leaps-and-bounds algorithm is an algorithm which is used to ?nd the optimal solution in problems which might have a large number of possible solutions. Begins by dividing the poss
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