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