Explore the core frameworks of random selection. These methods ensure that every unit in a population has a known, non-zero chance of selection, minimizing bias and enabling statistical generalization.
The foundational method where every individual has an equal and independent probability of being chosen. Ideal for highly homogeneous populations.
Selection occurs at regular intervals (the 'kth' element) from an ordered list. Provides a spread across the entire population list with higher efficiency.
The population is divided into subgroups (strata) based on shared characteristics. Random samples are then drawn from each stratum to ensure representation.
Used when populations are widely dispersed. The population is divided into clusters (often geographical), and entire clusters are randomly selected for study.