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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.
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
The statistical methods for estimation and inference which are based on a function of sample observations, probability distribution of which does not rely upon a complete speci?cat
Compound symmetry : The property possessed by the variance-covariance matrix of the set of multivariate data when its chief diagonal elements are equal to each other, and in additi
Principal components regression analysis is a process often taken in use to overcome the problem of multicollinearity in the regression, when simply deleting a number of the expla
Geographical information system (gis): The software and hardware configurations through which the digital georeferences are processed and displayed. Used to recognize the geograph
Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi
Difference b/w historigram and histogram
Grade of membership model: This is the general distribution free method for the clustering of the multivariate data in which only categorical variables are included. The model ass
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
Given: There are 4 jobs and 4 persons. The cost incurred for each person and each job is as follows: Persons Job 1 Job 2 Job 3 Job 4 A 10 9 21 11 B 15 12 25 17 C 12 10 20 12 D 17
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