Sampling

• target population


  group of people you are interested in studying
• sampling frame


  list of all the people in your target population
• sample


  smaller group of people form the target population
• representative


  it reflects all of the different types of people in the target population
• simple random sampling - (sampling methods)


  e.g. names out of a hat or use a random name generator

  Pros:

  • every participant has an equal chance of being selected
  • non-biased
  • quick and easy

  Cons:

  • may not be a representative sample
• systematic sampling - (sampling methods)


  involves using a 'system' to select participants from the sampling frame e.g. every 10th person

  Pros:

  • quick and easy
  • everyone has equal chance of being selected so not biased

  Cons:

  • may not be a representative sample
  • there may already be a system built into the sampling frame, so it may not work using another system on top of this
• stratified sampling - (sampling methods)

  separating the target population into categories based on certain characteristics

  Pros:

  • you can ensure a representative sample
  • non-biased

  Cons:

  • time consuming
  • may not have the info you need to divide people into categories
• opportunity sampling - (sampling methods)

  select your sample of participants from whenever is available at the time

  Pros:

  • quick and easy

  Cons:

  • may be biased
  • probably wont be representative - only certain types of people around at certain times of day
• volunteer sampling - (sampling methods)

  advertise for participants to volunteer to take part in your research

  Pros:

  • quick and easy

  Cons:

  • may be biased sample
  • probably wont be representative - likely to attract a certain type of person