sampling

• sample:

  • group selected from larger population
  • should be representative
• target population:

  • all people researchers want to generalise to
• random sample:

  • members of target population have equal chance of selection
  • list of all members, names assigned a number, names assigned through lottery method
• strengths of random samples:

  • more representative - no researcher bias
• weaknesses of random samples:

  • difficult and time consuming
  • still possible to get unrepresentative sample
  • refusal to take part
• opportunity sample:

  • select anyone who is willing and available
• strengths of opportunity samples:

  • more convenient
  • saves money, time and effort
• weaknesses of opportunity samples:

  • less representative, more bias
  • researcher bias - complete control over who they select
• volunteer sample:

  • participants select themselves
• strengths of volunteer samples:

  • easy, minimal effort from researchers
  • less time consuming
  • want to take part
• weaknesses of volunteer samples:

  • less representative, volunteer bias - attracts a certain type of people
• systematic sample:

  • every nth member of target population selected
  • sampling frame is produced, list organised into e.g alphabetical order
• strengths of systematic samples:

  • avoids researcher bias
  • fairly representative
• weaknesses of systematic samples:

  • time consuming + refusal to take part
  • not truly unbiased
• stratified sample:

  • identify subgroups that make up population
  • proportions for representative samples are worked out
  • people that make up subgroups are selected through random sampling
• strengths of stratified samples:

  • avoids researcher bias
  • representative
• weaknesses of stratified samples:

  • strata cant reflect all ways people are different
  • time consuming + refusal to take part