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Respondent-driven sampling (RDS): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. After participating the seeds are asked to recruit other people they know in target population. The sampling continues in this manner with the current sample members recruiting the next wave of the sample members until the desired sample size is achived. By using the mathematical model which weights the sample to compensate for the fact that the sample was collected in a non-random manner, the data provided by such a sampling scheme can be used to give asymptotically unbiased estimates about target population. An instance of the use of this approach is the estimation of the drug user's in New York who have HIV.
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
You may have the opportunity to buy some electronic components. These components may be reliable (1) or unreliable (2). The potential pro?ts are £10,000 if the components are rel
stationary time series
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
facts and statistics about daycare
Compound symmetry : The property possessed by the variance-covariance matrix of the set of multivariate data when its chief diagonal elements are equal to each other, and in additi
A theorem which shows that any counting process may be uniquely decomposed as the sum of a martingale and a predictable, right-continous process called the compensator, assuming ce
This is an alternative to the Newton-Raphson technique for optimization (finding out the minimum or the maximum) of some function, which includes replacing the matrix of second der
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
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