Cultural contexts: The most important consideration when designing a sampling strategy for a cultural context is to fit the sampling design to the research objectives.

It should be noted that the evaluation had some serious limitations, mostly related to the sampling design.

Stratified random sampling designs divide the population into homogeneous strata, and an appropriate number of participants are chosen at random from each strata.

Internal consistency checks are made between the sampling design and the outcome and rigorous data cleaning procedures are followed at the WVS data archive.

It uses a probability-based sampling design to represent the condition of all lakes in similar regions sharing similar ecological characteristics.

The method is a stratified-random sampling design, and is commonly used for a wide variety of statistical estimates, including exit polling for elections.

There appears to be no sampling design that covers all cases.

Extrapolation from the sample to the 3-D material is valid because of the randomness of the sampling design, so this is called design-based sampling inference.

Process: MMP uses a 3-stage sampling design to select an appropriate sample of persons from which locally and nationally representative data can be derived.

In the theory of finite population sampling, a sampling design specifies for every possible sample its probability of being drawn.