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The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approach does not need the number of mixture components to be known in before. The basic idea is that the Dirichlet procedure induces a prior distribution over the partitions of the data which can then be combined with the prior distribution over parameters and chance. The distribution over partitions can be generated incrementally using Chinese restaurant procedure.
MAZ experiments : The Mixture-amount experiments which include control tests for which the entire amount of the mixture is set to zero. Examples comprise drugs (some patients do no
Case-cohort study : The research design in epidemiology which involves the sampling of controls at the outset of the study that is to be compared with the cases from the cohort. Th
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
Designs which permits two or more questions to be addressed in the investigation. The easiest factorial design is one in which each of the two treatments or interventions are p
In the experimental studies, the collection of individuals to which the experimental process of interest is not applied. In the observational studies, most often used for a collect
Resentful demoralization is the possible phenomenon in the clinical trials and intervention studies in which comparison groups not attaining a perceived desirable treatment become
Mendelian randomization is the term applied to the random assortment of alleles at the time of gamete formation, a process which results in the population distributions of genetic
Reasons for screening data Garbage in-garbage out Missing data a. Amount of missing data is less crucial than the pattern of it. If randomly
Hamilton County judges try thousands of cases per year. In an overwhelming majority of the cases disposed, the verdict stands as rendered. However, some cases are appeale
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
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