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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 matrix for a set of stimuli, with the goal of making any structure in the data as transparent as possible. The goal of all such techniques or method is to find a low-dimensional space in which points in the space represent stimuli, one point representing one stimulus, such that the distances between points in the space match as well as possible in some sense the original dissimilarities or the similarities. In a very common sense this simply means that the larger the observed dissimilarity value (or smaller the similarity value) amongs two stimuli, the further apart should be the points representing them in derived spatial solution. A common approach to finding the required coordinate values is to select them so as to minimize some least squares type fit criterion such as follows
Why Graph theory? It is the branch of mathematics concerned with the properties of sets of points (vertices or nodes) some of which are connected by the lines known as the edges. A
The estimator of the group by the time period interaction in a study in which the subjects in two different groups are observed in two different time periods. Normally one of th
what is goal post mentality?
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
Probit analysis is the technique most commonly employed in the bioassay, specifically toxicological experiments where the group of animals is subjected to known levels of a toxin
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
It is the multivariate normal random vector which satisfies certain conditional independence suppositions. This can be viewed as a model framework which contains a wide range of st
You have probably noticed by now that some of the statements of necessary and sufficient conditions sound more natural than others. For example it seems more natural to express "We
how to describe association between quantitative and categorical variables
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