Примеры использования Simple random на Английском языке и их переводы на Русский язык
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Simple Random Sampling.
In each stratum a simple random sample of towns is taken.
Simple random, estimator 2.
Error calculation formulas are mainly based on simple random selection.
Simple random(or equal probability) sampling(SI);
Within each stratum, localities are selected using simple random sampling.
Simple random sampling by neighborhood of aged 50-64 years.
For small enterprises(enterprises with less than 5 employees) a simple random sampling is made.
Simple random sampling by district and age group of 15-19 years.
There is only one scalefactor for all cases, because the sample is a simple random sample.
Simple random sampling was applied to each stratum Table 3.
Systematic sampling is almost identical to simple random sampling if the population list is randomized.
Simple random sampling by neighborhood of age group of 10-14 years.
This survey was carried out using a sample of 3 270 households chosen by simple random sampling.
Suppose, for instance, you have a simple random sample of doctors who are members of the American Medical Association.
Under simple random sampling(without replacement) all possible samples have equal selection probabilities.
Cluster sampling of classes can be achieved either by simple random sampling or systematic random sampling.
Simple random sampling Each unit from the sampling frame has an equal probability of being selected and selection is entirely by chance.
For each stratum, the required number of outlets is drawn either by simple random sampling or by sampling probability proportional to size.
Whereas a simple random sample is subject to a single sampling error, a two-stage cluster sample is subject to two sampling errors.
For each commodity group, the required number of outlets was drawn either by simple random sampling or by sampling with probability proportional to size.
The choice is based on a simple random design for the selection of private household samples from population registers and the calibrated estimators.
Section 2 describes cut-off sampling andthree probability techniques: simple random sampling, stratified sampling and sampling proportional to size.
In a simple random sample, the unbiased estimate of the population standard deviation is just the sample standard deviation, only with n-1 in the denominator instead of the usual n.
Monte Carlo simulations of the sample spaces were carried out for simple random sampling of households with different sampling ratios and for area frame sampling.
Sampling during the survey is a simple random sample; therefore any person from the research target group had an equal chance of being selected by the survey sampling.
Then, a simulation allowed to estimate the relative efficiencies(compared with simple random sampling) for main crop area estimates and for crop area changes.
The strategy to adopt a simple random sampling of households from population registers and calibrated estimators produces accurate estimates and allow the reduction of non-sampling errors.
A proportionate stratified sample of classes may prove to be more precise than a simple random sample of classes, but sample size should not be reduced for the sake of such expected benefits.
First of all, the efficiency of Simple Random Sampling of HOUseholds from Administrative Register(SRSHOU) managed by municipalities was studied.