chapter 5 copyright © allyn & bacon 2008 this multimedia product and its contents are protected...

Chapter 5

Copyright © Allyn & Bacon 2008

This multimedia product and its contents are protected under copyright law. The following are prohibited by law:• Any public performance or display, including transmission of any image over a network;• Preparation of any derivative work, including the extraction, in whole or in part, of any images;• Any rental, lease, or lending of the program.

Discussion TopicsParticipants, subjects, and samplesProbability samplingNon-probability samplingIssues related to samplingCriteria for evaluating sampling procedures


Subjects, Participants, and SamplesParticipant or Subject

Person from whom data are collected The term “subject” is gradually being phased out It is being replaced by “participant” and “source of

data”Sample – the collective group of subjects or

participants from whom data are collected


Sampling ProceduresTwo types of procedures

Probability Statistically driven sampling techniques where the

probability of being selected is known Purpose is to select a group of participants representative of

the larger group of subjects from which they are selectedNon-probability

Pragmatically driven sampling techniques where the probability of being selected is not known

Purpose is to select participants who can be particularly informative about the research issues


Probability SamplingMethod of sampling in which participants are

selected randomly from a population in such a way that the researcher knows the probability of selecting each participant.In a sample of 10 from a population of 100, each subject

has a 10% chance of being included in the sampleIn a sample of 50 from a population of 100, each

participant has a 50% chance of being in included in the sample


Probability SamplingPopulation: a large group of individuals to whom

the results of a study can be generalizedTarget population: the group to whom the results are

intended to be generalizedSampling frame (i.e., survey population or accessible

population) The group to whom the researcher has access and from

which the actual sample will be drawn Often the sampling frame and the target population are

different


Probability SamplingThe goal of probability sampling is to select a

sample that is representative of the population from which it is selectedSampling error - the difference between the “true”

result and the “observed” result that can be attributed to using samples rather than populations

Sampling bias - the difference between the “observed” and “true” results that is attributed to the sampling mistakes of the researcher.


Probability SamplingTypes of probability techniques

Simple random - a number is assigned to each subject in the population and a table of random numbers or a computer is used to select subjects randomly from the population

Systematic - a number is assigned to each subject in the population, and every nth member of the population is selected



Stratified sampling - similar to random sampling with the exception that subjects are selected randomly from strata, or subgroups, of the population Strata: homogeneous subgroups within a population

Males and females Certified and non-certified teachers

Proportional stratified sample Disproportional stratified sampling



Cluster sampling: similar to random sampling except that naturally occurring groups are randomly selected first, then subjects are randomly selected from these sampled groups Useful when it is impossible to identify all of the

individuals in a population Typical educational clusters are districts, schools,

or classrooms


Probability SamplingFive steps in selecting probability samples

Define the target populationIdentify the sampling frameDetermine the sample sizeSelect the sampling strategy (i.e., procedure)Select the sample


Non-Probability SamplingMethod of sampling in which the probability

of selecting a participant is unknownIt is often not possible to use probability

sampling techniques due to access, time, resource or financial constraints

It is often desirable to select subjects who can be particularly informative about the research issues


Non-Probability Sampling

Three categories of non-probability sampling proceduresConvenience samplingPurposiveQuota


Non-Probability SamplingConvenience sampling: selecting a participant or

group of participants based on their availability to the researcherTypical of much educational research given the

constraints under which it is conductedThe major concern is the limited generalizability of the

results from the sample to any populationExamples

Students enrolled in the researcher’s classes Fourth-grade students in two local, parochial schools to

which the researcher has access


Non-Probability SamplingPurposive sampling: selection of particularly

informative or useful participantsTypically selects a few information-rich participants who

are studied in-depthAlso known as purposeful samplingExamples

It is reasonable to select “expert” teachers if one is trying to understand how teachers use effective instructional strategies

It is reasonable to select physically fit individuals if one is trying to identify effective exercise behaviors


Non-Probability SamplingQuota sampling: non-random sampling

representative of a larger populationUsed when the researcher cannot use

probability sampling procedures but does want a sample that is somewhat representative of the population

Similar to stratified sampling with the exception that the subjects are selected non-randomly


Non-Probability SamplingTypes of non-probability techniques

Typical case: selecting a representative participantExtreme case: selecting a unique or atypical participantMaximum variation: selecting participants to represent

extreme casesSnowball (i.e., network): selecting participants from

recommendations of other participantsCritical case: selecting the most important participants

to understand the phenomena being studied


Using Sampling ProceduresQuantitative studies

The desired use of probability sampling due to the ability to generalize the results to the larger population

Frequent use of non-probability techniques - particularly convenience sampling - due to access, time, resource, or financial constraints

Qualitative studies Almost exclusive reliance on non-probability techniques -

particularly purposeful sampling


Sampling and ResultsHow might the sampling procedures affect the

results?Need to identify the sampling procedure usedNeed to evaluate the sampling procedure in light of

the research problems and conclusionsNeed to consider the strengths and weaknesses of

specific sampling procedures (see Table 5.2, p. 123)


Sampling and ResultsSampling error: the difference between the “true”

result and the “observed” result that can be attributed to using samples rather than populations In a sample of 99 from a population of 100

The observed result is likely to be very, very close to the true result

Sampling error is minimal In a sample of 2 from a population of 100

The observed result is likely to be somewhat different from the true result

Sampling error is high


Sampling and ResultsSampling bias: the difference between the

“observed” and “true” results that is attributed to the sampling mistakes of the researcher Deliberately sampling participants with certain

attributes Positive attitudes High self-esteem High level of achievement

Using participants from different populations and assigning them to different treatment groups Males to an experimental treatment group and females to a

traditional treatment group


Sampling and ResultsHow might the characteristics of the

participants affect the results?Volunteer samples

Different characteristics between volunteers and non-volunteers can lead to different responses Educational level Socio-economic status Need for social approval Conformity

Commonly used due to their availability


Sampling and Results

Subject motivation Specific characteristics of the sample can

predispose them to respond in certain ways Only selecting teachers using holistic language

strategies would likely predispose them to respond favorably to an attitudinal scale focusing on holistic language instruction

Only selecting students who participate in extra-curricular activities might predispose them to certain types of responses


Sampling and ResultsSample size - general rules of thumb

Quantitative studies 30 participants for correlational research 15 participants in each group for experimental research Approximately 250 responses for survey research

Qualitative studies - a sufficient number of participants are needed to ensure that no new information is forthcoming from additional cases


Sampling and Results

Sample SizeNeed to interpret results very carefully -

results form studies using very large or very small samples can be misleading Results indicating “no difference” or “no

relationship” in studies with small samples an be problematic

Results of “differences” or “relationships” in studies can be problematic


Criteria for Evaluating Sampling Procedures

Participants should be described clearly with specific and detailed information related to demographic and other personal characteristics

The population should be clearly defined.The sampling procedure should be clearly

described.



The return rate should be reported and analyzed.Less than a 60% return rate requires

further analysisComparison of the responses of respondents

to non-respondentsThe selection of participants should be

free of bias.



Selection procedures should be appropriate for the problem being investigated.

Adequate sample sizes should be used.Qualitative studies should have

informative and knowledgeable subjects.


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