Chapter%205:%20Subjects,%20Participants,%20and%20Sampling

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Chapter 5 Subjects, Participants, and Sampling

• EDUC 502
• September 26, 2005

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Subjects, Participants, and Samples

• Subject or participant person from whom data are
  collected
• Subject term used in a quantitative context
• Participant term used in a qualitative context
• Sample the collective group of subjects or
  participants from whom data are collected

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Types of sampling procedures

• Probability
• Statistically driven sampling techniques where
  the probability of being selected is known
• Purpose is to select a group of subjects
  representative of the larger group of subjects
  from which they are selected
• Non-probability
• Pragmatically driven sampling techniques where
  the probability of being selected is not known
• Purpose is to select subjects who can be
  particularly informative about the research
  issues

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Probability sampling

• Method of sampling in which subjects are selected
  randomly from a population in such a way that the
  researcher knows the probability of selecting
  each subject
• In a sample of 10 from a population of 100, each
  subject has a 10 chance of being included in the
  sample
• In a sample of 50 from a population of 100, each
  subject has a 50 chance of being in included in
  the sample

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Population a large group of individuals to whom
the results of a study can be generalized

• Target population the group to whom the results
  are intended to be generalized
• Sampling 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
• The target population could be all fourth graders
  in Orleans Parish the sampling frame is fourth
  graders in public schools in Orleans Parish
  (i.e., excluding private and parochial school
  students due to their inaccessibility)

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Drawing Representative Samples

• Sampling 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 (i.e., that determined using the
  sample) is likely to be very, very close to the
  true result (i.e., that determined using all 100
  subjects in the population). Sampling error is
  minimal.

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Drawing Representative Samples

• On the other hand, 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.

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Drawing Representative Samples

• Sampling bias the difference between the
  "observed" and "true" results that is attributed
  to the sampling mistakes of the researcher.
• Deliberately sampling subjects with certain
  attributes (e.g., positive attitudes, high
  self-esteem, high level of achievement, etc.)
• Using subjects from different populations and
  assigning them to different treatment groups
  (e.g., males to an experimental treatment group
  and females to a traditional treatment group)

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Illustration Random Rectangles

• Keep the handout turned over!!! Dont look at it
  until told.
• Turn over the handout and scan it for 5 seconds.
• Estimate the average area for one of the
  rectangles. Write your estimate on a piece of
  paper.
• Pass the piece of paper over to your neighbor.
• Pool estimates as a class. Record on TI-83.

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Illustration Random Rectangles

• Using the TI-83, select 3 of the numbered
  rectangles on the sheet.
• Calculate the mean of the 3 rectangles.
• Using the TI-83 once again, select 10 of the
  numbered rectangles on the sheet.
• Calculate the mean of the 10 rectangles.
• Report your results to the rest of the class to
  form a pooled set of data.

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Illustration Random Rectangles

• Compare the means of L1, L2, and L3 against the
  actual mean area of the rectangles.
• What are the reasons that L1 does not match the
  actual mean? What are the reasons L2 and L3 dont
  match the actual mean?
• Discussion question Construct an example of a
  situation in educational research that would
  match the random rectangles scenario.

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Possible Scenarios

• A researcher wants to determine the percentage of
  students in a school who live in poverty and does
  so by approaching students at random in the
  hallway and asking if they receive free or
  reduced lunch (sampling bias).
• A researcher wants to determine the average level
  of mathematics achievement in a county and does
  so by calculating the mean test scores for a
  random sample of five students (sampling error).

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Types of Probability Sampling Procedures

• 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
• Stratified sampling similar to random sampling
  with the exception that subjects are selected
  randomly from strata, or subgroups, of the
  population. Strata are homogeneous subgroups
  within a population (e.g., males and females
  low, middle and high socio-economic status
  certified and non-certified teachers working with
  special needs students etc.)

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Types of Probability Sampling Procedures

• Cluster sampling similar to random sampling
  except that naturally occurring groups are
  randomly selected first, then subjects are
  randomly selected from the sampled groups
• Useful when it is impossible to identify all of
  the individuals in a population
• Typical educational clusters are districts,
  schools, or classrooms
• Example - 27 of the 54 school districts were
  randomly selected, one secondary school in each
  district was randomly selected, and students
  randomly selected from each school were tested

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Non-Probability Sampling

• Method of sampling in which the probability of
  selecting a subject is unknown
• It 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 (e.g., if the researcher is trying to
  understand how teachers use manipulatives, it
  makes sense to select teachers who do use these
  in their classes)
• The goal of non-probability sampling is to
  identify information-rich participants

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Types of Non-Probability Sampling

• Convenience sampling selecting a subject or
  group of subjects based on their availability to
  the researcher
• Typical of much educational research given the
  constraints under which it is conducted
• The major concern is the limited generalizability
  of the results from the sample to any population
• Examples
• Students enrolled in the researcher's classes
• Fourth-grade students in two local, parochial
  schools to which the researcher has access

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Types of Non-Probability Sampling

• Purposive sampling selection of particularly
  informative or useful subjects
• Typically selects a few information-rich subjects
  who are studied in-depth
• Also known as purposeful sampling
• Examples
• It is reasonable to select "expert" teachers if
  one is trying to understand how teachers use
  effective teaching strategies
• It is reasonable to select physically fit
  individuals if one is trying to identify
  effective exercise behaviors

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The use of probability and non-probability
sampling

• Quantitative 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

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Criteria for evaluating subjects and sampling
procedures

• Subjects or 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 selection of subjects should be free of bias.
  
• Selection procedures should be appropriate for
  the problem being investigated.

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Criteria for evaluating subjects and sampling
procedures

• Adequate sample sizes should be used.
• Qualitative studies should have informative and
  knowledgeable subjects.
• IMPORTANT Keep all of these criteria in mind in
  constructing your proposal, keeping in mind which
  ones apply to predominantly quantitative studies
  and which to predominantly qualitative.

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Homework Exercises

• Textbook pp. 121-122 (1, 3, 10, 13)

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Class Exercise

• Respond to the following questions related to the
  Reducing Teacher Stress and Kindergarten
  Readiness and Retention articles found in Chapter
  13 of the text.
• What is the population and sampling procedure
  used in the Reducing Teacher Stress article?
  Describe the sample in terms of its size and the
  characteristics of the subjects.
• What is the sampling procedure used in the
  Kindergarten Readiness and Retention article?
  Describe the sample in terms of the
  characteristics of the subjects..
• What did the researchers accomplish by using
  different procedures?