4.4.5—Sampling methods

A sample is a selected subset of a target population. Random sampling gives each member a known equal chance of selection; quota sampling fills predefined category proportions; convenience sampling selects people who are easiest to reach. They trade representativeness, cost, speed and access.

Sampling error and bias arise when some groups are over- or under-represented, when people self-select or when the sampling frame excludes likely customers. Larger samples reduce random error but not systematic bias.

Define the population and selection rule, then ask who had a chance to be included and whether the sample mirrors the target.

To study commuters, a random sample requires a usable passenger list or selection frame; a quota sample can ensure specified proportions by travel time or age; a convenience survey taken only at 9 a.m. is quick but may miss night-shift workers and other groups.

A large convenience sample can be less reliable than a smaller, well-designed sample.