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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.
Geometric distribution: The probability distribution of the number of trials (N) before the first success in the sequence of Bernoulli trials. Specifically the distribution is can
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
Group visible design is an arrangement of the v mn treatments in b blocks such that: * Each block comprises k distinct treatments k5v; * Each treatment is replicated r number
Likert scales is often used in the studies of attitudes in which the raw scores are based on the graded alternative responses to each of a series of queries. For instance, the sub
An oil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The company
Linearity - Reasons for Screening Data Many of the technics of standard statistical analysis are based on the assumption that the relationship, if any, between variables is li
Q1: The growth in bad debt expense for Aptara Pvt. Ltd. Company over the last 20 years is as follows. 1997 0.11 1998 0.09 1999 0.08 2000 0.08 2001 0.1 2002 0.11 2003 0.12 2004 0.1
Reasons for screening data Garbage in-garbage out Missing data a. Amount of missing data is less crucial than the pattern of it. If randomly
Mean squarederror is the expected value of square of the difference between an estimator and the true value of the parameter. If the estimator is unbiased then the mean of the squ
Kalman filter : A recursive procedure which gives an estimate of the signal when only the 'noisy signal' can be observed. The estimate is efficiently constructed by putting the exp
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