Sampling

 Sampling methods that allow us to know in advance how likely it is that any element of a population will be selected for the sample  Major Types  Simple random sampling  Systematic random sampling  Cluster sampling  Stratified random sampling

 Identifies cases strictly on the basis of chance  True random sample is obtained through the equal probability of selection method (EPSEM)  All members of population have equal chance of being sampled

 Determine the number to sample, for example, a sample of 125 from a population of 700  Calculate sampling interval  population / sample size. Round to next lowest whole number  700 / 125 = 5.6  5  Select first element randomly (usually from a list), and then select every n th element. Here, select every 5 th member of population  In almost all sampling situations, systematic random sampling yields what is essentially a simple random sample – except in populations or sampling frames with periodicity  Periodicity - the sequence of elements of the population varies in some regular, periodic pattern

 Cluster - naturally occurring, mixed group of elements of the population; each element (person, for instance) appears in one and only one cluster at one time  Prisons are clusters for sampling inmates  City blocks are clusters for sampling residents  Useful when sampling frame (a definite list of elements) is not available or too expensive to cover  Large populations spread out across a wide geographic area  “Hidden” populations  Also called “multi-stage cluster sampling” because…

1. Distinguish all elements in the population (i.e., in the sampling frame) according to their value on some relevant characteristic (police officer rank, for instance: captains, lieutenants, sergeants, patrol officers, etc.). That characteristic forms the sampling strata. Each element must belong to one and only one stratum 2. Sample elements randomly from within each strata: e.g., 25 captains, 25 sergeants, etc. Strata – layers, levels, groups (singular is stratum) Purpose: to ensure that various groups will be included in the sample. Useful when researcher needs to make sure that small groups are included

 Each member of population has UNequal probability of selection  Four types  Availability - select units that are available  Quota  Purposive/judgment  Snowball

 Elements are selected because they are available or easy to find  Also known as a haphazard, accidental, or convenience sampling Examples:  Interviewing people on a street corner or at the mall  Surveying students in a classroom  Magazine surveys  Observing conversations in an on-line chat room

 Intended to overcome the most obvious flaw of availability sampling—that the sample will just consist of whoever or whatever is available, without any concern for its similarity to the population of interest  Distinguishing feature is that quotas are set to ensure that the sample represents certain characteristics in proportion to their prevalence in the population

 Each sample element is selected for a purpose, usually because of the unique position of the sample elements  May involve studying the entire population of some limited group (directors of shelters for homeless adults) or a sub-set of a population (prison unit managers with a reputation for having the respect of both prisoners and staff)  May be a “key informant survey,” which targets individuals who are particularly knowledgeable about the issues under investigation (a neighborhood leader familiar with local street drug markets)

 Useful for hard-to-reach or hard-to-identify populations for which there is no sampling frame, but the members of which are somewhat interconnected (at least some members of the population know each other)  Can be used to sample members of such groups as drug dealers, prostitutes, practicing criminals, participants in Alcoholics Anonymous groups, gang leaders, informal organizational leaders, homeless persons, and other “hidden populations”