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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.
Suppose we estimate the following model: Passengersi = 1 + 2Populationi + ui a) Generate a scatter plot with passengers on the vertical axis and population on the horizonta
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.
The variables appearing on the right-hand side of equations defining, for instance, multiple regressions or the logistic regression, and which seek to predict or 'explain' response
Pie chart is an extensively used graphical technique for presenting relative frequencies related with the observed values of the categorical variable. The chart comprises of a cir
Quota sample is the sample in which the units are not selected at the random, but in terms of a particular number of units in each of a number of categories; for instance, 10 men
Respondent-driven sampling (RDS ): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. Aft
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
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