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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, if suitable, to a different cluster in an attempt to optimize some predefined numerical criterion that measures in some sense the 'quality' of cluster solution. Several such clustering criteria have been suggested, but the most usually used arise from considering the features of the within groups, between groups and whole matrices of sums of squares and the cross products (W, B, T) which can be described for every partition of the observations into the particular number of groups. The two most ordinary of the clustering criteria developing from these matrices are given as follows
minimization of trace W
minimization of determinant W
The first of these has tendency to produce the 'spherical' clusters, the second to produce clusters that all have same shape, though this will not necessarily be spherical in shape.
how to find the PDF and CDF of a gamma random variable with given equation?
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Radical statistics group : The national network of the social scientists in United Kingdom committed to the critique of statistics as taken in use in the policy making procedure. T
The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:
Human height growth curves : The growth of human height is, in common, remarkably regular, apart from the pubertal growth spurt. The satisfactory longitudinal development curve is
Regression discontinuity design is the quasi-experimental design in which participants in, for instance, an intervention study, are assigned to the treatment and control groups on
how does it work exactly
difference between histogram and historigram
Looking for the correct answer.Y=50+.079(149)-.261(214)=
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
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