samplingsdesignet

Samplingsdesignet refers to the plan that guides how a sample is drawn from a population for statistical inference. It specifies who should be included, how individuals are selected, how many are chosen, and how the process handles nonresponse and potential biases. The choice of sampling design affects representativeness, precision of estimates, and the feasibility and cost of data collection.

A typical sampling design includes the target population, the sampling frame, the sampling method, the allocation of the sample across subgroups, and procedures for weighting and analysis. Designs can be probability-based, where each element has a known chance of selection, or non-probability-based, where selection depends on practical considerations. Examples of probability designs include simple random sampling, stratified sampling, cluster sampling, and systematic sampling. Non-probability designs include convenience and purposive sampling. Probability designs allow estimation of sampling error and construction of confidence intervals; non-probability designs often rely on model-based adjustments to mitigate bias.

In Danish statistical usage, the term samplingsdesignet is not widely used in formal texts; related concepts are described with terms such as udtagningsdesign or stikprøve-design, which refer to planning the data collection and sampling strategy in surveys and experiments.

Because the design influences data quality, researchers often conduct pretests, consider frame completeness, and account for weighting and design effects during analysis.