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Population Sampling Methods

Population Sampling Methods. Yesenia Villar-Villalobos IS 280 11/12/09 Prof. Richardson. Defining a Population.

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Population Sampling Methods

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  1. Population Sampling Methods Yesenia Villar-Villalobos IS 280 11/12/09 Prof. Richardson

  2. Defining a Population • “A population must be specific enough to provide readers a clear understanding of the applicability of your study to their particular situation and their understanding of that same population” (Dale, 2006)

  3. How important is validity and reliability?

  4. “Gives all members of the population a known chance of being selected for inclusion in the sample and this does not depend upon previous events in the selection process” (Birchall, 2009) Probability Sampling: Simple Random Systematic Stratified Cluster Probability Sampling

  5. Simple Random Sampling • Define the population • Determine percentage to be interviewed or studied • Each individual has an equal chance of selection • Random sample becomes representative of the larger whole

  6. Systematic Sampling • Every nth element from a list (sample interval) • List must be in random order

  7. Stratified Sampling • Classify the population in sub-populations (strata) based on well-known characteristics • Ex: Age, gender, socio-economic status, etc. • Randomly chose a sample from sub-populations • Either proportional or disproportional

  8. Cluster Sampling • Randomly select groups (strata) rather than individuals • Multi-stage sampling • Useful when no elements within a population is available • Final sample may not be representative of the population

  9. Nonprobability Sampling • “Members are selected from the population in some nonrandom manner” (Barreiro, 2009) • ● Nonprobabilty Sampling: • – Convenience • – Purposive • – Quota

  10. Convenience Sampling • Exploratory research • Inexpensive approximation • Ex: preliminary research efforts to attain a gross estimate • Saves time and money

  11. Purposive Sampling • “The person who is selecting the sample is who tries to make the sample representative, depending on his opinion or purpose, thus being the representation subject” (Barreiro, 2009) • Subjective judgment (Judgment Sampling) • Requires researcher confidence that the sample truly represents an entire population

  12. Quota Sampling • Nonprobability equivalent of stratified sampling • Convenience or judgment sampling to fill quota from specific sub-groups of a population • Ex: Interviewer is instructed to interview 50 males between the ages of 18-25 • Useful when: • Time is limited • Money restraints • Detailed accuracy is not important

  13. Calculating a Sample Size • Rule of thumb: “the larger the sample size, the more closely your sample data will match that from the population” (Birchall, 2009) • Key factors to consider: • How accurate you wish to be • How confident you are in the results • What budget you have available

  14. Sample Size Calculators • http://www.surveysystem.com/sscalc.htm • http://www.ezsurvey.com/samplesize.html • http://www.macorr.com/ss_calculator.htm

  15. References • Barriero, P.L. and Albandoz, J.P, “Population and sample. Sampling techniques,” http://optimierung.mathematik.uni-kl.de/mamaeusch/veroeffentlichungen/ver_texte/sampling _en.pdf. • Birchall, Joanne, “Sampling and Samples,” http://www.market researchworld.net/index.php?option=com_content&task=view&id=23&Itemid=41. • Dale, Dennis, “Population Sampling Methods for Research Studies: Definitions and Uses,” http://www.associatedcontent. com/article/28368/population_sampling_methods_for_research.html. • StatPac Inc.,“Sampling Methods,” http://www.statpac.com/ surveys/sampling.htm.

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