SAMPLING

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SAMPLING

• EDUCATIONAL RESEARCH

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WHY SAMPLE?

• Not needed when can access entire population.
• Must sample when not feasible to access entire
  population.

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Sample Should Be Representative of the Larger
Population...
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IMPORTANT TERMS

• Sample--subset of people selected to study
• Population--larger group from which sample comes
  to which we will infer

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STEPS IN SAMPLING

• ID ideal/preferred population
• Identify accessible population
• Use Principle of Sampling

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Principle of Sampling

• If sample is representative of accessible
  population, findings can be generalized to
  population
• Generalizing from sample to population involves
  risks

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TYPES OF SAMPLING PROCEDURES

• Probability
• Nonprobability

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PROBABILITY SAMPLING

• Participants drawn by chance (random)
• Every member has known probability of being
  chosen (110 1100)
• EPSEM--equal probability of selection method

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Probability Sampling Types

• Simple Random Sampling
• Two-Stage Random Sampling
• Stratified Sampling
• Cluster Sampling
• Systematic Sampling

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SIMPLE RANDOM SAMPLING

• All have equal and independent chance of selection

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Performing Random Sampling

• Define and list ALL population members
• Assign each a from 0 to ????
• Group columns of digits according to needed
• Two digits for s up to 99
• Three digits for s up to 999

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Performing Random Sampling

• Arbitrarily select a in the random number table
• If selected corresponds to of member of
  identified population, member is in sample
• go down list
• repeat above selection method until desired of
  participants obtained

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Two-Stage Random Sampling

• Useful in large populations
• Select random clusters
• Select random individuals from random clusters

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STRATIFIED SAMPLING

• Information known about total population prior to
  sampling
• Know population subgroups/strata
• Distinguish all elements in population according
  to value on characteristic(s)

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Performing Stratified Sampling

• Identify subgroups/strata
• Select randomly a specific of subjects from
  each stratum
• Revisit random sampling

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Cluster Sampling

• Unit chosen is NOT an individual, but a group of
  individuals naturally together
• Constitute a cluster
• Are alike with respect to characteristics
  relevant to the study

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Performing Cluster Sampling

• Chosen at random from population of clusters
• All members of clusters chosen must be included
  in sample
• Using clusters as individuals, follow steps
  outlined in random sampling

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Examples of Cluster Sampling

• Schoolsclusters for sampling students
• Blocks clusters for sampling residents
• Counties clusters for sampling general
  populations
• Businessesclusters for sampling employees

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SYSTEMATIC SAMPLING

• Convenient to draw a random sample when
  population elements are arranged sequentially

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Systematic Sampling

• Variation of simple random sampling
• Different choices not independent
• Yields simple random sample in most, but NOT all,
  sampling situations
• If sequence varies in regular, periodic pattern,
  then will not have a random sample---rarely occur

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Performing Systematic Sampling

• Determine size of sample
• Divide sample into population
• Randomly select starting point
• Select every nth subject
• Need 5 people, have 45 in pop, select every 9th
  person once starting point chosen

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Nonprobability Sampling

• Probability of selection of population elements
  is NOT known.
• Participants NOT chosen by chance
• Cannot estimate likelihood selection
• More convenient and economical

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NONPROBABILITY SAMPLING TYPES

• Accidental Purposive
• Quota Snowball
• Convenience
• Cannot expect representative sample using
  nonprobability methods

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ACCIDENTAL SAMPLING

• Haphazard, availability, or convenience
• Interviewing/surveying first X number of
  individuals encountered
• EXTREMELY weak, but fairly popular
• Most psych research is accidental

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PURPOSIVE SAMPLING

• Subjects judged to be representative are chosen
  from larger population
• Doesnt produce representative sample
• Results may be misleading

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PURPOSIVE SAMPLING

• Each sample selected for purpose, usually because
  of unique position of sample element
• Used in national elections (referred to as
  bell-weather districts)

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QUOTA SAMPLING

• Selection of typical cases from diverse strata of
  a population
• Must know characteristics of entire population to
  set right quotas
• Approximation of population with respect to
  selected characteristics

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SNOWBALL SAMPLING

• Useful for hard to reach or identify, but
  interconnected populations
• May consider when cannot think of another method
• Generalizations are very tentative

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Performing Snowball Sampling

• Identify one member of a population
• Speak with member
• Ask member to identify others
• Speak with those members
• Ask those members to identify more
• and so on and on and on....

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Snowball Sampling Examples

• drug dealers
• prostitutes
• practicing criminals
• gang leaders
• Alcoholics Anonymous members

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CONVENIENCE SAMPLING

• When random is impossible
• Individuals who are available
• Likely to be biased
• Not representative of any population
• Should be avoided if possible
• Should be replicated

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Sample Representativeness

• Sampling Goal representativeness
• Larger the sample, more confidence we have in
  representativeness of sample
• More homogeneous the population, the more
  confidence of representativeness

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