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Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification might then be determined according to a simple majority verdict among those much similar or 'nearest' training set subjects, that is a subject would be assigned to the group to which the majority of the 'neighbours' belonged. Simple nearest neighbour techniques just consider the most similar neighbour. More common methods consider the k nearby neighbours, where k>1.
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also
Intercropping experiments are the experiments including growing two or more crops at same time on the same patch of land. The crops are not required to be planted nor harvested at
Morbidity is the term used in the epidemiological studies to describe sickness in the human populations. The WHO Expert Committee on the Health Statistics noted in its sixth repor
Ordination is the procedure of reducing the dimensionality (that is the number of variables) of multivariate data by deriving the small number of new variables which contain much
Recursive models are the statistical models in which the causality flows in one direction, that is models which include only unidirectional effects. Such type of models do not inc
Institutional surveys are the surveys in which the primary sampling units are the institutions, for instance, hospitals. Within each of the sampled institution, a sample of the pa
Paul Jordan has just been hired as a management analyst at Digital Cell Phone Inc. Digital Cell manufactures a broad line of phones for the consumer market. Paul's boss, John Smith
difference between histogram and historigram
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
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