mba, Advanced Statistics

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

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Recursive models, Recursive models are the statistical models in which the...

Recursive models are the statistical models in which the causality flows in one direction, that is models which include only unidirectional effects. Such type of models do not inc

Curvature measures, The diagnostic tools or devices used to approach the cl...

The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan

Definition, what is operational gaining

what is operational gaining

Latin square, Latin square  is an experimental design targeted at removing ...

Latin square  is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment ef

Describe length-biased sampling, Length-biased sampling : The bias which ar...

Length-biased sampling : The bias which arises in the sampling scheme based on the visits of patient, when some individuals are more likely to be chosen than others simply because

Continual reassessment method, Continual reassessment method: An approach ...

Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic

Dropout, A subject who withdraws from the study for whatever reason, advers...

A subject who withdraws from the study for whatever reason, adverse side effects, noncompliance, moving away from the district, etc. In number of cases the reason may not be known.

Network sampling, Network sampling is a sampling design in which the simpl...

Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of th

The breusch-pagan test, The Null Hypothesis - H0:  There is no heteroscedas...

The Null Hypothesis - H0:  There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >

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