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Prior distributions: The probability distributions which summarize the information about a random variable or parameter known or supposed at a given time instant, prior to attaining further information from the empirical data. It is used almost entirely within the context of Bayesian inference. In any specific study a variety of such kind of distributions might be assumed. For instance, reference priors represent the minimal prior information; clinical priors are used to formalize the opinion of well-informed specific individuals, frequently those taking part in the trial themselves. Lastly, sceptical priors are used when the large treatment differences are considered unlikely.
Morbidity is the term used in the epidemiological studies to describe sickness in the human populations. The WHO Expert Committee on the Health Statistics noted in its sixth repor
The approach of controlling the error rate in an exploratory analysis where number of hypotheses are tested, but where the strict control which is provided by multiple comparison p
The distribution over distributions in the sense that each draw from the process is itself the distribution. The name Dirichlet process or procedure is due to the fact that the ?ni
Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
Buffon's needle problem : A problem proposed and solved by the scientist Comte de Buffon in 1777 which includes determining the probability, p, which a needle of length l will inte
Knox's tests: These tests designed to detect any tendency for the patients with a particular disease to form the disease cluster in time and space. The tests are relied on a two-b
A radically different approach of dealing with the uncertainty than the traditional probabilistic and the statistical methods. The necessary feature of the fuzzy set is a membershi
A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
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