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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.
what is measures of variability?
The division of a sample of observations into several classes, together with the number of observations in each of them. It acts as a useful summary of the main features of the da
Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th
Weathervane plot is the graphical display of the multivariate data based on bubble plot. The latter is enhanced by the addiction of the lines whose lengths and directions code the
ACC – A pioneer in the Indian cement industry Associated Cement Companies Ltd. (ACC) came into existence in 1936, after the merger of 10 companies belonging to four important bus
Hanging rootogram is he diagram comparing the observed rootogram with the ?tted curve, in which dissimilarities between the two are displayed in relation to the horizontal axis,
Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are
Bartlett decomposition : The expression for the random matrix A which has a Wishart distribution as the product of the triangular matrix and the transpose of it. Letting each of x
Item-total correlation is an extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
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