Sampling Examples (Chapter 5)

Convenience Sampling

Non-probability samplers are often used in practice because in many applications, it is not possible to generate a sampling frame. We select individuals into our sample by any convenient contact. This type of sampling is useful for preliminary data. They should not be used for statistical inference as they are generally not constructed to be representative of any specific population.

Cluster Sampling

Select a random sample of groups (e.g. schools in a state) then collect data from every object in the groups. This technique is more economical than the rand selection.

Stratified Sampling

We split the population into non-overlapping groups or strata and then sample within each strata. Sampling within each strata can be by simple random sampling or systematic sampling. It is important to note that we sample every individual in each strata.

Systematic Sampling

We start with the complete sampling frame and members of the population are assigned unique identification numbers. However, in this type of sampling every third or fifth person is selected. The spacing or interval between selections is determined by the ratio of the population size to the sample size (N/n). Hardly used in practice.

Simple Random Sampling

We start with what is called the sampling frame, a complete list or enumeration of the entire population. Each member of the population is assigned a unique identification number, and then a set of numbers are selected at random to determine the individuals to be included in the sample. The probability that any individual is selected into the sample is 1/N.