sampling

• Population


  The group of people from whom the sample is drawn
• Sampling methods

  • Opportunity sampling
  • Random sampling
  • Systematic sampling
  • Stratified sampling
  • Volunteer sampling
• Time sampling


  • Reduces the number of observations that has to made so it is less time consuming
  • The small amount of data that you collect within that time frame ends up being unrepresentative of the observation as a whole
• Event sampling

  • Good for infrequent behaviours that are likely to be missed if time sampling was used
  • If complex behaviour is being observed, important details of the behaviour may be overlooked by the observer
  • If the behaviour is very frequent, there could be counting errors
  • It is difficult to judge the beginning and ending of a behaviour
• opportunity sampling


  participants happen to be available at the time when the study is being carried out, so they are recruited conviently
• strengths opportunity sampling

  • time saving
  • less costly
  • easy to do
• limitations of opportunity sampling

  • not representative of wider population - lacks generalisability
  • researcher bias is presented as they control who they want to select
• random sampling

  all members of the population have the same equal chances of being selected
• method of random sampling


  each member of the population is assigned a number and a random number generator is used to randomly to choose the participant
• strengths of random sampling

  no researcher bias - researcher has no influence of who is picked
• limitations of random sampling

  • time consuming - need to have a list of members in the sampling frame and it takes time to contact them
  • volunteer bias - participants can refuse to take part so can end up with an unrepresentative sample
• systematic sampling

  a predetermined system where members of the target population are selected at regular intervals

  K=N/n

  • K = systematic sampling interval
  • N = population size
  • n = sample size
• strengths of systematic sampling

  • avoids researcher bias
  • assuming the order or list is randomised, then this method offers an unbiased chance of gaining a representative sample
• limitations of systematic sampling

  • if order isn't randomised, there can be a bias - eg. if every nth person was male, there would only be males in the study
  • doesn't give an equal chance of selection
• stratified sampling


  researchers divide subjects into subgroups (strata) based on characteristics they share

  the created sample should contain members from each key characteristics in a proportionate representative of the target population
• strengths of systematic sampling

  • more accurate and diverse data
  • avoids problem of misrepresentation caused by random sampling
  • no researcher bias
• limitations of systematic sampling

  • time consuming - requires more planning
  • lacks versatile and is harder to analyse as its more detailed
• volunteer sampling

  involves self selection where the participant has volunteered themselves for the study
• strengths of volunteer sampling

  • achieves a large sample by reaching a wide audience
  • easy to access
  • little effort required
  • cheap
  • as participants are willing to take part, they are more likely to cooperate in the study
• limitations of volunteer sampling

  • those who volunteer may all display similar characteristics - increases chances of an unrepresentative sample
• snowball sampling


  recruited participants recruit other subjects for study
• strengths of snowball sampling

  • self selective - time saving
  • researchers can access 'hidden populations'
• limitations of snowball sampling

  • researchers have little control over selection - minimal knowledge if the sample is representative of the target population
  • possible bias - participants may choose others who are similar to themselves
• target population


  desired population subgroup to be studied