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Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizing some numerical index of the clustering. Since it is not possible to consider every partition of n individuals into g groups (because of the enormous number of the partitions), the algorithm starts with some given initial partition and considers individuals in turn for moving into the other clusters, creating the move if it causes an improvement in the value of the clustering index. The procedure is continued until no move of the single individual causes an improvement.
Atomistic fallacy : A fallacy which arises because of the association between two variables at the individual level might vary from the association between the same two variables m
Post stratification adjustmen t: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplie
Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow t
The approach to statistics based on a frequency view of probability in which it is supposed that it is possible to consider an in?nite sequence of the independent repetitions of th
Cohort study : An investigation in which the group of individuals (or the cohort) is identi?ed and followed prospectively, possibly for many years, and their subsequent medical his
Non central distributions is the series of probability distributions each of which is the adaptation of one of the standard sampling distributions like the chi-squared distributio
Half-normal plot is a plot for diagnosing the model inadequacy or revealing the presence of outliers, in which the absolute values of, for instance, the residuals from the multipl
This term sometimes is applied to the model for explaining the differences found between naturally happening groups which are greater than those observed on some previous occasion;
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
Classification matrix: A term many times used in discriminant analysis for the matrix summarizing the results and outputs obtained from the derived classi?cation rule, and obtaine
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