The Logic Of Sampling Key Terms

1
Chapter 7

• The Logic Of SamplingKey Terms

2

• Nonprobability samplingTechnique in which
  samples are selected in a way that is not
  suggested by probability theory.

3

• Purposive (judgmental) sampling Selecting a
  sample based on the knowledge of a population,
  it's elements and the purpose of the study.

4

• Snowball samplingResearcher collects data on
  members of the target population that can be
  located, then asks those individuals to provide
  the information to locate other members.

5

• Quota samplingUnits are selected into a sample
  on the basis of prespecified characteristics, so
  the total sample will have the same distribution
  of characteristics assumed to exist in the
  population being studied.

6

• Probability samplingSamples are selected in
  accord with probability theory, typically
  involving some random selection mechanism.

7

• RepresentativenessQuality of a sample having the
  same distribution of characteristics as the
  population from which it was selected.

8

• EPSEMEqual probability of selection method.
• ElementUnit about which information is collected
  and that provides the basis of analysis.

9

• PopulationThe theoretically specified
  aggregation of study elements.
• Study populationAggregation of elements from
  which the sample is actually selected.

10

• Random selectionEach element has an equal chance
  of selection independent of any other event in
  the selection process.
• Sampling unitElement or set of elements
  considered for selection in some stage of
  sampling.

11

• ParameterSummary description of a given variable
  in a population.
• StatisticSummary description of a variable in a
  sample.

12

• Sampling errorThe degree of error to be expected
  of a given sample design.
• Confidence levelExpression of the accuracy of
  sample statistics.

13

• Confidence intervalRange of values within which
  a population parameter is estimated to lie.
• Sampling frameList or quasi list of elements
  from which a probability sample is selected.

14

• Simple random samplingBasic sampling method
  assumed in the statistical computations of social
  research.
• Systematic samplingEvery kth element in the
  total list is chosen for inclusion in the sample.

15

• Sampling intervalStandard distance between
  elements selected in the sample.
• Sampling ratioProportion of elements in the
  population that are selected.

16

• StratificationGrouping of units composing a
  population into homogenous groups before sampling.

17

• Cluster samplingA multistage sampling in which
  natural groups are sampled initially with the
  members of each selected group being subsampled
  afterward.

18

• PPSProbability proportionate to size.
• WeightingGiving some cases more weight than
  others.