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The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial intelligence and machine learning, and presentation of the information extracted in a form that is without difficulty understandable to humans. Significant biological discoveries are now frequently made by combining data mining methods with the traditional laboratory techniques; an instance is the discovery of novel regulatory areas for heat shock genes in C. Elegans made by mining vast amounts of the gene expression and sequence data for the significant patterns.
It is used generally for the matrix which specifies a statistical model for a set of observations. For instance, in a one-way design with the three observations in one group, tw
Basic reproduction number : A term used in the theory of infectious diseases for the number of secondary cases which one case would generate in a completely susceptible population.
Cluster randomization : The random allocation of the groups or clusters of the individuals in the formation of treatment groups.Eeven though not as statistically ef?cient as the in
importance of mathamatical expection in business
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
The transformation of the Pearson's product moment correlation coefficient, r, can be given by The statistic z has the normal distribution with mean here ρ is the pop
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
Mosaic displays is the graphical display of the standardized residuals from the fitting a log-linear model to a contingency table in which the colour and outline of the mosaic's '
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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