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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.
Item-total correlation is an extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c
The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for
The number of employees absent from work at a large electronics manufacturing plant over aperiod of 106 days is given in the table below. 146 141 139 140 145 141 142 131 142 140
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Chernoff's faces : A method or technique for representing the multivariate data graphically. Each observation is represented by the computer-created face, the features of which are
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
work sheet within answer
Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional
Randomized response technique : The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what quer
Mardia's multivariate normality test is a test that a set of the multivariate data arise from the multivariate normal distribution against departures due to the kurtosis. The test
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