7. Logic of Sampling

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7. Logic of Sampling

• Jin-Wan Seo, Professor
• Dept. of Public Administration,
• University of Incheon

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7. Logic of Sampling

• Sampling
• Social researchers must select observations that
  will allow them to generalize to people and
  events not observed. Often this involves
  sampling, a selection of people to ob serve. The
  process of selecting observation is _____________.

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7. Logic of Sampling

• Sampling in social research has developed hand in
  hand with political polling.
• Famous poll conducted by the Literary Digest
  (18901938) in 1920
• mail postcard to people in 6 states, asking them
  who they were planning to vote for in the
  presidential race between Warren Harding and
  James Cox.
• names are selected for the poll from telephone
  directories and automobile registration lists
• Based on the postcards sent back, the Digest
  correctly predicted that Harding would be
  elected.
• In the election that followed, the Digest
  expanded the size of its poll and made correct
  predictions in 1924, 1928, and 1932.

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7. Logic of Sampling

• In 1936, the Digest conducted its most ambitious
  poll.
• Over two million people from ten million
  responded, giving the Republican contender, Alf
  Landon, a stunning 57 to 43 percent landslide
  over the incumbent, President Franklin Roosevelt.
• Two weeks later, voters gave Roosevelt a second
  term in office by the largest landslide in
  history, with 61 percent of the vote. Landon won
  only 8 electoral votes to Roosevelts 523.
• Why? Sampling problems exclusion of poor
  people.
• The poor voted predominantly for Roosevelts New
  Deal recovery program. The Digests poll may have
  correctly represented the voting intentions of
  telephone subscribers and automobile owners.
• George Gallup correctly predicted that Roosevelt
  would beat Landon. His success in 1936 hinged on
  his use of something called quota sampling.
• Gallup and his American Institute of Public
  Opinion used quota sampling to good effect in
  1936, 1940, and 1944.

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7. Logic of Sampling

• In 1948, failure of the Gallup
• In 1948, Gallup and most political pollsters
  predicted that Governor Thomas Dewey of New York
  would win the election over the incumbent
  President Harry Truman.
• Why? Sampling problems too unrepresentativeness
  of his samples
• Quota sampling which had been effective in
  earlier years was Gallups undoing in 1948.
• This technique requires that the researcher know
  something about the total population in this
  case, the population of voters.
• For national political polls, such information
  came primarily census data. By 1948, however,
  World War II had produced a massive movement from
  the country to cities, radically changing the
  character of the U.S. population from what the
  1940 census showed, and Gallup relied on 1940
  census data.
• City dwellers, moreover, tended to vote
  Democratic hence the overrepresentation of rural
  votes in his poll had the effect of
  underestimating the number of Democratic votes.

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7. Logic of Sampling

• Probability Sampling Nonprobability Sampling
• Sometimes you can and should select
  _____________ sampling using precise statistical
  techniques as the primary method of selecting
  large, representative samples for social science
  research including national political polls.
• At the same time, probability sampling can be
  impossible or inappropriate in many research
  situation. In this case, __________________
  sampling techniques are more appropriate.

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7. Logic of Sampling

• 1. Reliance on available sampling
• Relying on available subjects, such as stopping
  people at a street corner or some other location,
  is an extremely risk sampling method.
• This methods does not permit any control over
  the representativeness of a sample.
• It is 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 use of this method is justified on
  grounds of feasibility, researchers must exercise
  great caution in generalizing from their data.
  Also, they should alert readers to the risks
  associated with this method.

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7. Logic of Sampling

• 2. _______________ or judgmental sampling
• Sometimes its appropriate to select a sample on
  the basis of knowledge of a population and the
  purpose of the study.
• In the initial design of a questionnaire, for
  example, you might with to select the widest
  variety of respondents to test the broad
  applicability of questions. Although the study
  findings would not represent any meaningful
  population, the test run might effectively
  uncover any peculiar defects in your
  questionnaire. This situation would be considered
  a pretest, however, rather than a final study.

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7. Logic of Sampling

• 3. Snowball sampling
• A form of ___________________
• This procedure is appropriate when the members
  of a special population are difficult to locate,
  such as homeless individuals, migrant workers, or
  undocumented immigrants.
• The researcher collects data on the few members
  of the target population, he or she can locate,
  then ask those individuals to provide the
  information needed to locate other members of
  that population whom they happen to know.
• Snow ball refers to the process of
  accumulation as each located subject suggests
  other subjects.

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7. Logic of Sampling

• 4. Quota sampling
• Quota sampling begins with a matrix, or table,
  describing the relevant characteristics of the
  target population.
• Once you have created such a matrix and assigned
  a relative proportion to each cell in the matrix,
  you proceed to collect data from people having
  all the characteristics of a given cell. You then
  assign a weight to all the people in a given cell
  that is appropriate to their portion of the total
  population.
• Inherent problems (differ from _____________
  sampling)
• the quota frame must be accurate and it is often
  difficult to get up-to-date information for this
  purpose
• the selection of sample elements within a given
  cell may be biased even if its proportion of the
  population is accurately estimated.

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7. Logic of Sampling

• Key
• The key to probability sampling is _____________
  selection.
• Probability sampling methods provide an
  excellent way of selecting representative samples
  from large, known populations.
• Problems
• These methods counter the problems of conscious
  and unconscious sampling bias by giving each
  element in the population a known probability of
  selection.
• The most carefully selected sample will never
  provide a perfect representation of the
  population from which it was selected. There will
  always be some degree of sampling error.
• Probability sampling methods make it possible to
  estimate the amount of sampling error expected in
  a given sample by predicting the distribution of
  samples with respect to the target parameter.

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7. Logic of Sampling

• 1. Simple random sampling
• logically the most fundamental technique in
  probability sampling, but it is seldom used in
  practice.
• 2. Systematic sampling
• involves the selection of every kth member from
  a sampling frame. This method is more practical
  than simple random sampling, and, with a few
  exceptions, it is functionally equivalent.

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7. Logic of Sampling

• 3. _________________ sampling
• Stratification, the process of grouping the
  members of a population into relatively
  homogeneous strata before sampling, improves the
  representativeness of a sample by reducing the
  degree of sampling error.
• 4. Multistage cluster sampling
• a relatively complex sampling technique that is
  frequently used when a list of all the members of
  a population does not exist. Typically,
  researcher must balance the number of clusters
  and the size of each cluster to achieve a given
  sample size.
• Stratification can be used to replace the
  sampling error involved in multistage cluster
  sampling.

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