What is the primary feature of probability sampling?

The primary feature of probability sampling is that it involves selecting samples from a known population in such a way that each member of the population has a known, non-zero chance of being included in the sample. This method is crucial for ensuring that the sample accurately reflects the characteristics of the larger population, thus allowing for generalizations and statistical inferences to be made effectively.

In probability sampling, tools such as random number generators or other techniques are used to ensure that the selection process is unbiased and representative. This contrasts significantly with non-probability sampling methods, where the likelihood of selection is not known, which may lead to bias and limit the ability to apply findings to the broader population.

Understanding this foundational aspect of research methodology highlights why a well-defined and known population is essential for drawing valid conclusions from collected data. It underscores the importance of rigorous sampling techniques in fields that rely on statistical analysis and generalization of findings to larger groups.