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6030 - Introduction to Educational Research > Chapter 4 > Flashcards

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When the unit of data is an individual, we refer to that individual as a participant


______________ means the same thing as participant



_________________ always use the term participant

Qualitative studies



is the collection of participants from whom data have been collected in a study


population (or target population or universe)

is the group of individuals to whom we wish to generalize the results of our study


Delimiting variables

the characteristics (e.g., gender, grade, subject matter) that define the population


Survey population or Sampling frame

the list of actual individuals you will choose your sample from. While the population may be theoretical, the survey population must be finite


Random Sampling

A technique in which each member of the survey population has an equal chance of appearing in the sample. Random sample will represent their populations if the sample size is large enough.


Margin of Error

An interval within which the true population value lies. Typical values are 95% and 99% confidence intervals.


Simple Random Sampling

Every member of the population is enumerated. The sample is randomly selected from this list.


Systematic Sampling

Every nth element of the sampling frame is selected for inclusion in the sample.


________________ can be biased if some characteristic of the sampling frame is related to the sampling cycle. So if you choose every 30th student, and class sizes are just over 30, you may always choose a student in the back of the class.

Systematic sampling


Stratified Sampling

Certain characteristics (i.e., strata) of the population are identified for representation in the sample. Once the strata are identified, they are represented in the sample at the same percentage as they exist in the population (proportional stratified sample). The strata are filled through a random sampling procedure. It is also possible to represent strata in percentage different than they exist in the population (e.g., whites and blacks at 50% each; disproportional stratified sampling). This might be done when certain subgroups are to be compared in later analyses.


Cluster Sampling

The sampling of naturally occurring groups (i.e., clusters) of participants. Participants can then be drawn randomly from the sampled clusters (e.g., students from within classrooms). This procedure works, but special statistical techniques (e.g., hierarchical linear modeling) must be used to analyze the data, since participants from within a cluster are more similar to each other than participants from different clusters.


In non-probability sampling . . .

the probability of each individual in the survey population being included in the sample is not equal.


________________ typically use non-probability sampling techniques

Qualitative studies


Convenience Sampling

The sample is selected because of its easy availability. Typically, convenience samples will be biased.


Quota Sampling

Basically, this is a stratified sampling approach in which the strata are filled with convenience samples rather than random samples.


Purposive Sampling (or Judgment or Judgmental Sampling)

The research selects participants because they will be particularly informative about the topic under investigation.


Criterion Sampling

Participants are selected on the basis of identified characteristics that will provide needed information


Typical Case Sampling (Model Instance Sampling)

Participants are selected on the basis of being “typical” or “representative”


Extreme Case Sampling

Participants are selected on the basis of being “unique” or an “outlier”


Maximum Variation Sampling (Maximum Heterogeneity Sampling)

Participants are selected to represent both ends of a continuum under investigation


Snowball Sampling (Network Sampling)

One begins with a few participants, and these participants nominate other participants, and these recommend still other participants. This creates an obvious lack of independence among the participants.


Critical Case Sampling

Participants are chosen on the basis of a dramatic example of the phenomenon being studied


Purposeful Random Sampling

A random sample of small size from the population is used as a purposeful sample


Concurrent Sample

Two independent samples are taken concurrently: a random sample for the quantitative part of the study, and a purposeful sample for the qualitative part


Multilevel Sampling

Samples are taken that are representative of different levels of aggregation that comprise the overall population (e.g., district, school, and classroom). This is sometimes called nested, because groups are contained within one another.


Stratified Purposeful Sampling

Type I: First collecting a stratified probability sample, and then taking a purposeful subsample from this original stratified sample
Type II: First collecting a purposeful sample, and then stratifying this sample on a variable of interest, and finally taking a subset of the original sample using the stratification variable as part of the selection process


volunteer sample

Volunteers differ in systematic ways from non-volunteers: They: are better educated, have higher SES, are more intelligent, have greater need for approval, are more sociable, are more unconventional, are less authoritarian, and less conforming