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Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of stimuli, for instance, judges and soft drinks, and asymmetric proximity matrices, for instance, citations of journal A by journal B and vice versa. Unfolding was introduced as a manner of representing judges and stimuli on a single straight line so that the rank-order of the stimuli as determined by each of the judge is reflected by the rank order of the distance of stimuli to that judge.
K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
Procrustes analysis is a technique of comparing the alternative geometrical representations of a group of multivariate data or of the proximity matrix, for instance, two competing
Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
Household interview surveys : The surveys in which the primary sampling units are typically geographic regions such as nations or cities. For each such unit sampled, there are addi
1. define statistical algorithms 2. write the flow charts for statistical algorithms for sums, squares and products. 3. write flow charts for statistical algorithms to generates ra
Q. A toothpaste company want to know if its new product increases the length of time in-between dentist visit to its user. The company sets a target for 180 days to determine if it
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
Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of succes
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