Probability Sampling

How will you sample?

The first step in probability sampling is identifying the population you would like to generalize to. Then, you develop a sampling frame from which to draw a fair sample from that population and conduct your research with the sample. You calculate the significance of results and finally generalize your results back to the population. Following is an explanation of common terms used in all probability sampling304:


  • Population: The population is the set of people or entities to which findings will be generalized. The population must be defined explicitly before a sample is taken and findings must not be generalized beyond the population.
  • Sample: The units that will be included in the study, for example people, organizations, neighbourhoods.
  • The sampling frame: A list of everyone in the population, from which the sample is drawn. It is often difficult to generate complete lists, for example telephone directories are often used as sampling frames but tend to under-represent the poor (who have fewer or no phones) and the wealthy (who have unlisted numbers). Think about the ways that you can address any bias in your sampling frame.
  • Sample size: The number of cases needed in the sample.  This can be calculated based on the  of the population and the level of confidence that you would like in your findings (for social science studies the confidence level is generally 5% and for medical studies the confidence level is generally 1%). (for small populations, under 2,000, the size of the population also affects the sample size needed).  
  • Significance: is the percent chance of concluding there is a relationship in the data when there is none. Using the general social scientists cutoff of .05: if there is 5% or less chance that a relationship is just due to chance, we conclude the relationship is real.


For an online site that will help you calculate the sample size needed see


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