Chapter 7: The Logic of Sampling

simple random sampling

is the basic sampling method assumed in the statistical computations of social research.Once a sampling frame has been properly established,to use simple random sampling the researcher assigns a single number to each element in the list,not skipping any number in the process.Simple random sampling is not feasible and may not be the most accurate method available.

reliance on available subjects

relying on available subjects,such as stopping people at a street corner or some other location, is sometimes called "convenience" or "haphazard" sampling. This is a common method for journalists, but it is an extremely risky sampling method for social research.This method does not permit any control over the representativeness of a sample.Justified only if the researcher wants to study the characteristics of people passing the sampling point at specified times or if less-risky sampling methods are not feasible.Even when this method is justified on grounds of feasibility, researchers must exercise great caution in generalizing from their data.They should also alert readers to the risks associated with this method.

sampling unit (a part of random selection)

that element or set of elements considered for selection in some stage of sampling.REASONS FOR USING RANDOM SELECTION:FIRST,this procedure serves as a check on conscious or unconscious bias on the part of the researcher.Random selection offers access to the body of probability theory, which provides the basis for estimating the characteristics of the population as well as estimating the accuracy of samples.

stratified sampling

(based on the second factor in sampling theory) Rather than selecting a sample from the total population,at large,the researcher ensures that appropriate numbers of elements are drawn from homogenous subsets of the population.The choice of stratification variables typically depends on what variables are available.You should be concerned primarily with those that are presumably related to variables you want to represent accurately.

EPSEM

(equal probability of selection method)a sample design in which each member of a population has the same chance of being selected into the sample.Seldom if ever perfectly represent the populations from which they are drawn.Probability sampling offers two special advantages.FIRST,probability samples although never perfectly representative,are typically more representative than other types of samples, because the biases previously discussed are avoided.probability sample is more likely than a nonprobability sample to be representative of the population from which it is drawn.SECOND,important,probability permits us to estimate the accuracy or representativeness of the sample.Probability sampling ensures that samples are representative of the population we wish to study,Probability sampling rests on the use of a random-selection procedure.

snowball sampling

(some consider to be a form of accidental sampling) a nonprobability sampling method,often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing.This procedure is appropriate when the members of a special population are difficult to locate, such as the homeless,migrant workers,or undocumented immigrants.The researcher collects data on the few members of the target population he or she can locate,then asks those individuals to provide the information needed to locate other members of that population whom they happen to know."Snowball" refers to the process of accumulation as each located subject suggests other subjects.Because this procedure also results in samples with questionable representativeness,it's used primarily for exploratory purposes.Snowball sampling can be more than a simple technique for finding people to study,it can be a revealing part of the inquiry.

Quota Sampling (Continued)

Although quota resembles probability sampling, it has several inherent problems.First,the quota frame (the proportions that different cells represent) must be accurate,and it's often difficult to get up to date information for this purpose.(This is what caused Truman the election in 1948).Second,the selection of sample elements within a given cell may be biased even though its proportion of the population is accurately estimated.The logic of quota sampling can sometimes be applied usefully to a field research project.

Representativeness and Probability of Selection

Representativeness-That quality of a sample of having the same distribution of characteristics as the population from which it was selected.It is enhanced by probability sampling and provides for generalizability and the use of statistics.For our purpose,a sample is representative of the population from which it is selected if the aggregate characteristics of the sample closely approximate those same aggregate characteristics in the population.Note that,samples need not be representative in all respects,representativeness is limited to those characteristics that are relevant to the substantive interests of the study.However,you may not know in advance which characteristics are relevant.A BASIC PRINCIPLE OF PROBABILITY SAMPLING IS THAT:a sample will be representative of the population from which it is selected if all members of the population have an equal chance of being selected in the sample.

Selecting Informants

Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.NOT TO BE CONFUSED WITH RESPONDENT.Are especially important to anthropologists,also important to other social researchers as well.Were they limited to specific jobs or did their information cover many aspects of the operation?This and other criteria helped determine how useful the informant might be.Select informants typical to what you are studying. Because they are willing to work with investigators,informants will almost always be somewhat "marginal" or atypical within their group.Informants' marginality may not only be biased, but it could limit their access to the different sectors of the community you wish to study.

The Theory and Logic of Probability Sampling

The general term for samples selected in accord with probability theory,typically involving some random-selection mechanism.Types of probability sampling include EPSEM,PPS,simple random sampling, and systematic sampling.Nonprobability sampling methods cannot guarantee that the sample we observed is representative of the whole population.Involves sophisticated statistics.If all members of a population were exactly the same,there would be no need for careful sampling procedures.FUNDAMENTAL IDEA BEHIND PROBABILITY SAMPLING IS THIS:To provide useful descriptions of the total population,a sample of individuals from a population must contain essentially the same variations that exist in the population.

Random Selection

a sampling method in which each element has an equal chance of selection independent of any other event in the selection process.ULTIMATE PURPOSE OF SAMPLING:to select a set of elements from a population in such a way that descriptions of those elements accurately portray the total population from which the elements are selected.Probability sampling enhances the likelihood of accomplishing this aim and also provides methods for estimating the degree of probable success.

Quota Sampling

a type of nonprobability sampling in which units are selected into a sample on the basis of prescribed characteristics,so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied.Like probability sampling,quota sampling addresses the issue of representativeness, although the two methods approach the issue differently.Quota sampling begins with a matrix,or table,describing the characteristics of the target population.Depending on research purposes,you may need to know what proportion of the population are male as well as female.Knowing what proportions of each sex fall into various age categories,educational levels,ethnic groups,and so forth.You might also need to know what proportion is urban,eastern,male,under 25,white,working class,and the like and all possible combinations of these attributes.Once the matrix is created and assigned a relative proportion to each cell,you proceed to collect data from people having all the characteristics of a given cell.A weight is assigned to their portion of the total population.When all the sample elements are so weighted,the overall data should provide a reasonable representation of the total population.

purposive (judgmental) sampling

a type of nonprobablility sampling in which the units to be observed are selected on the basis of the researcher's judgment about which ones will be the most useful or representative.Field researchers are often particularly interested in studying deviant cases,cases that don't fit into fairly regular patterns of attitudes and behaviors inorder to improve their understanding of the more-regular pattern.Selecting deviant cases for study is another example of purposive study.In qualitative research projects, the sampling of subjects may evolve as the structure of the situation being studied becomes clearer and certain types of subjects seem more central to understanding than others do.

nonprobability sampling

any technique in which samples are selected in some way not suggested by probability theory.

systematic sampling

every kth element in the total list is chosen (systematically) for inclusion in the sample.To ensure against any possible human bias in using this method,you should select the first element at random.Is virtually identical to simple random sampling.Slightly more accurate than simple random sampling.SAMPLING INTERVAL:is the standard distance between elements selected in the sample.SAMPLING RATIO:is the proportion of elements in the population of elements in the population that are selected.

element

is that unit about which information is collected and that provides the basis of analysis.In survey research, elements are people or certain kinds of people.Other kinds of units can contribute like:families,social clubs,or corporations might be the element of study.Elements are often the same as units of analysis,though the former are used in the sample selection and the latter in data analysis.