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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.
Calibration : A procedure which enables a series of simply obtainable but inaccurate measurements of some quantity of interest to be used to provide more precise estimates of the r
Average age at death : A ?awed statistic summarizing expectancy of the life and other aspects of the mortality. For instance, a study comparing average age at the death for male sy
Hello-goodbye effect : The phenomenon initially described in psychotherapy research, but one which might arise whenever a subject is assessed on two occasions, with some interventi
The time series for RESI1, HI1 and COOK1 have appeared again with different outlier values even though the 17 outliers found early were removed.
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
Probability distribution : For the discrete random variable, a mathematical formula which provides the probability of each value of variable. See, for instance, binomial distributi
Mention the characteristics of Statistics. Explain any two applications of Statistics.
importance of time series on the number of babies given birth
A theorem which shows that any counting process may be uniquely decomposed as the sum of a martingale and a predictable, right-continous process called the compensator, assuming ce
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
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