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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.
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
Completeness : A term applied to a statistic t when there is only one function of that the statistic which can have the given expected value. If, for instance, the one function of
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Buffon's needle problem : A problem proposed and solved by the scientist Comte de Buffon in 1777 which includes determining the probability, p, which a needle of length l will inte
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
This term sometimes used to describe the extra factor in variance of the sample mean when n sample values are drawn without the replacement from the finite population of size N. Th
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
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