Which of the following sampling methods is based on probability?

Question

Accepted Answer

Probability sampling requires that every member of the target population has a known, non-zero chance of selection, ensuring mathematical objectivity and minimizing bias. This methodology relies on randomization mechanisms to draw representative samples, allowing researchers to accurately generalize findings back to the broader population. Unlike non-probability frameworks, it establishes statistical precision, making it essential for hypothesis testing and quantitative rigor in educational research designs.

Correct Option (Option 4):
Stratified sampling divides a heterogeneous population into distinct, non-overlapping homogeneous groups called strata based on specific shared attributes. A random sampling technique is then applied within each individual stratum to select the final participants. This guarantees that minor subgroups are adequately represented proportionally, combining non-probability-like grouping structures with strict probability-based selection methods.

Incorrect Option (Option 1):
Convenience sampling relies on gathering data from population members who are most conveniently accessible to the researcher. It does not utilize any system of random selection, making it a non-probability sampling method. This technique introduces substantial selection bias because individuals are chosen based on proximity rather than statistical design. Consequently, findings cannot be reliably generalized to the larger target population.

Incorrect Option (Option 2):
Quota sampling involves segmenting the population into groups and non-randomly choosing participants until a predetermined target number is reached. While it attempts to mirror the population's demographic distribution, the selection within those groups relies entirely on convenience or researcher choice. Because randomization is absent, it remains classified as a non-probability technique. It fails to give all eligible individuals an equal or calculable probability of being chosen.

Incorrect Option (Option 3):
Judgement sampling, also known as purposive sampling, depends entirely on the researcher's personal expertise and subjective criteria to handpick specific individuals. Participants are selected because they possess specific characteristics or perspectives relevant to the study's focus. This reliance on human judgment overrides any mathematical chance of selection, disqualifying it from probability sampling frameworks. The approach inherently risks researcher bias and lacks statistical generalizability.