sampling

• Sampling


  When researchers conduct studies and then publish findings, it's tempting to think the findings apply to all of us. But we need to think carefully about who exactly took part in the study, and if the behaviour of those participants can be generalised to everyone.
• Sampling techniques


  • Random
  • Systematic
  • Stratified
  • Opportunity
  • Volunteer
• Target population


  Every individual that forms part of the group you plan to study
• Generalisation


  Applying the results from a sample back to the target population
• Random sampling


  • Everyone in the population has the same chance or probability to be selected as a member of the sample
  • Researcher first needs a list of all members of the population
  • Can use methods like putting names in a hat and drawing them out or assigning numbers and using a random number generator
• Strength of random sampling

  • Avoids researcher bias
• Weakness of random sampling

  • Could randomly get an unrepresentative sample, maybe not representing all minority groups
  • Time consuming for large populations
• Systematic sampling


  • Go down the list of the population and choose every 5th or 10th or Nth person
• Strengths of systematic sampling


  • Removes chance for researcher bias
  • Quick way of getting a sample with small populations and existing lists
• Weakness of systematic sampling


  • Still possible to get an unrepresentative sample
  • Difficult with large populations to get a full list of members
• Opportunity sampling


  • Researcher simply includes anyone in the sample that they can get their hands on by asking them to take part
• Strength of opportunity sampling


  • Much faster way of getting a sample than other methods, could save money and allow researcher to complete study faster
• Weaknesses of opportunity sampling


  • Potential for researcher bias as researcher decides who to ask and who not to ask
  • Sample is likely not representative as researcher only has access to a limited section of the population, usually young university students
• Volunteer/self-selecting sampling


  • Participants select themselves, they volunteer themselves after seeing an advert
• Strength of volunteer/self-selecting sampling

  • Researcher can reach a large number of potential participants by using an advertisement, especially in a popular newspaper
  • Relatively easy to collect as participants put themselves forward
• Weakness of volunteer/self-selecting sampling

  • Volunteer bias, people who volunteer for studies are a certain type of person - helpful and have the time to take part, but we want to include people who are unhelpful and busy
• Stratified sampling


  • Creates a sample that is representative of the population as a whole
  • Researcher first identifies subgroups or strata and their proportion in the wider population
  • Then randomly selects participants from within each strata so they are represented in the same proportion in the final sample
• Strengths of stratified sampling


  • Sample is representative of the larger population, meaning we can be confident in generalising what we find to the population
  • Avoids researcher bias as it randomly selects participants from within each strata
• Weakness of stratified sampling

  • Researcher decides what strata are important to consider, meaning there may be some bias in the selection of strata
  • Time consuming and difficult
• Most psychology studies have been completed on WEIRD participants - Western, Educated, Industrial, Rich and Democratic - leading to concerns about whether the findings generalise around the world
• Historical studies often ignored or underrepresented women, leading to gender bias in much of accepted psychological theory