What is a probability sample

Answer

A probability sample is a sample selected from a population using a random process in which every member of the population has a known, non‑zero chance of being chosen. This method is used so that the sample is more likely to be representative of the whole population and so that statistical inferences (like confidence intervals and hypothesis tests) are valid.​

Key features

• Selection is based on randomization (for example, random number generators or random draws), not personal judgment or convenience.​

• Every unit in the population has a known probability of selection, which may be equal (simple random sampling) or unequal but still known (some complex survey designs).​

• Because probabilities are known, researchers can quantify sampling error and generalize results from the sample to the wider population.​

Common types

• Simple random sample: Each member of the population has exactly the same chance of being selected.​

• Systematic sample: Starting from a random point in an ordered list, every $k$-th unit is selected (for example, every 10th person).​

• Stratified sample: The population is divided into subgroups (strata) such as age or region, and random samples are drawn from each stratum.​

• Cluster sample: The population is split into clusters (for example, schools or villages), some clusters are chosen at random, and then all or a sample of units within those clusters are studied.​

Why it matters

Probability samples are considered the “gold standard” when researchers want unbiased, generalizable results, such as in national surveys, clinical research, and opinion polls. In contrast, non‑probability samples (like convenience or quota samples) do not give every member a known chance of selection, which limits how confidently results can be generalized to the whole population.

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