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Bayesian network: It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network comprises the following:
* A set of directed edges between the variables and a set of variables.
* Each variable has the ?nite set of the states which are mutually exclusive.
* The variables together with directed edges forma the conditional independence of the graph.
* To each of the variable A with parents B1; ... ; Bn there is an attached conditional probability table Pr A B1; B2; ... ; Bn .
An instance is shown in the Figure drawn below in which cancer is independent of age group given exposure to the toxics and smoking.
Concordant mutations test : A statistical test used in the cancer studies to determine whether or not a diagnosed second primary tumour is biologically independent of the original
Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent
Over dispersion is the phenomenon which occurs when empirical variance in the data exceeds the nominal variance under some supposed model. Most often encountered when the modeling
difference between histogram and historigram
The skewness is a measure of asymmetry and as it is positive at 4.29, it is greater than zero which reveals that the tail extends to the right indicating the distribution to be mor
The Null Hypothesis - H0: There is autocorrelation The Alternative Hypothesis - H1: There is no autocorrelation Rejection Criteria: Reject H0 (n-s)R 2 > = (1515 - 4) x (0.
Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a
Continuous variable : The measurement which is not restricted to the particular values except in so far as this is constrained by the accuracy of measuring instrument. General exam
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0 i =0, 1, 2, 3
Locally weighted regression is the method of regression analysis in which the polynomials of degree one (linear) or two (quadratic) are used to approximate regression function in
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