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Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing inclusion probabilities might result from some inherent feature of sampling process, or they might be deliberately imposed in order to attain better estimates by including 'more important' units with the higher probability. The unequal inclusion probabilities required to be accounted for in order to come up with the reasonable estimates of the population quantities. An instance of such a design is line-intercept sampling of the vegetation cover, in which the size of the patch of vegetation is measured whenever the randomly selected line intersects it. The larger the patch, the higher will be probabilities of inclusion in sample. This kind of sampling might be carried out by assigning to each unit the interval whose length is equal to the required probability and selecting random numbers from uniform distribution: a unit is involved if the random number is in its interval.
Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variab
Non-randomized clinical trial is the clinical trial in which the series of consecutive patients receive a new treatment and those which respond (according to some of the pre-defin
Healthy worker effect : The occurrence whereby employed individuals tend to have lower mortality rates than those who are unemployed. The effect, which can pose the serious problem
Higher criticism is a multiple-comparison test concept arising from the situation where there are number of independent tests of significance and interest lies in the rejecting jo
Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo
Ordered alternative hypothesis is a hypothesis or assumption which speci?es an order for the set of parameters of interest as an alternative to the equality, rather than simply th
hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
The interplay of the genes and environment on, for instance, the risk of disease. The term represents the step away from the argument as to whether the nature or nurture is the pre
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