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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.
Catastrophe theory : A theory of how little is the continuous changes in the independent variables which can have unexpected, discontinuous effects on the dependent variables. Exam
Bioassay : It is an abbreviation of biological assay, which in its classical form includes an experiment conducted on biological material to determine relative potency of test and
Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
Thomas Economic Forecasting, Inc. and Harmon Econometrics have the same mean error in forecasting the stock market over the last ten years. However, the standard deviation for Thom
Ascertainment bias : A feasible form of bias, particularly in the retrospective studies, which arises from the relationship between the exposure to the risk factor and the probabil
properties of chebyshevs lemma
Principal components analysis is a process for analysing multivariate data which transforms original variables into the new ones which are uncorrelated and account for decreasing
Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the
The plot of the number of cases of the disease against the time period. A large and sudden increase corresponds to an epidemic. The example of this is shown in the figure drawn bel
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