mba, Advanced Statistics

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Mention the characteristics of Statistics. Explain any two applications of Statistics.

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Bayesian network, Bayesian network : It is essentially an expert system in ...

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 c

Explain laplace distribution, Laplace distribution : The probability distri...

Laplace distribution : The probability distribution, f(x), given by the following formula   Can be derived as the distribution of the difference of two independent random var

Response feature analysis, Response feature analysis is the approach to th...

Response feature analysis is the approach to the analysis of longitudinal data including the calculation of the suitable summary measures from the set of repeated measures on each

Explain perturbation theory, Perturbation theory : The theory useful in ass...

Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo

Independent or Dependent variable, Whats the independent variable in the fo...

Whats the independent variable in the following sentence? -1) In a drug prevention program for boys and girls, will family-participation result in effective drug use reduction?

Bayes factor, Bayes factor : A summary of evidence for the modelM1 against ...

Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post

Explain negative hyper geometric distribution, Negative hyper geometric dis...

Negative hyper geometric distribution : In sampling without replacement from the population comprising of r elements of one kind and N - r of another, if two elements corresponding

Helmert contrast, Helmert contrast is the contrast often used in analysis ...

Helmert contrast is the contrast often used in analysis of the variance, in which each level of a factor is tested against average of the remaining levels. So, for instance, if th

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