sampling

• target population

  The group that the researchers draws the sample from and wants to be able to generalise the findings to.
• researchers conduct their experiments on a smaller sample of participants, taken from the larger population
• generalisation

  when the results/behaviour of the sample are assumed to apply to all the members of the target population
• whether the results can be generalised or not depends on how representative the sample is of the target population.
• representative sample

  a sample of the target group with a similar distribution of relevant characteristics, allowing us to generalise from the sample to the target group 
• unrepresentative sample

  A sample that does not reflect the distribution of characteristics of the target group, cannot be generalised to the target population, and is therefore biased.
• random sampling

  each member of the target population has a mathematically equal chance of being in the experiment's sample
• how is random sampling conducted?

  1. researcher needs full list of the entire target population
  2. all names are entered into a container or computer generator
  3. a number of names equal to the sample required are pulled from the container
  4. the names selected form the sample
• random sampling strengths

  • a random sample avoids researcher bias as the researcher can't choose the participants they want to form the sample, avoiding the possibility the researcher picks participants they feel are likely to give a preferred result
• random sampling weaknesses

  • by chance, participants could be picked that produce an unrepresentative sample e.g. too many members of the same gender
  • it can be hard and time-consuming to get a full list of a large target population
• systematic sampling

  A system is chosen for selecting from a target group, e.g. every Nth person in a list could be used in the sample. It differs from random sampling as it does not give an equal chance of selection to each individual in the target group
• how to conduct a systematic sample

  1. researcher needs full list of the entire target population
  2. the researcher reads down the list selecting every Nth participant to form the sample
  3. this process is continued until the sample number required is chosen
• systematic sampling strengths

  • avoids researcher bias as the researcher can't pick the participants they want in their sample
  • it can be quick if there is already an existing full list of the target population e.g. a school register
• systematic sampling weaknesses

  • if the target population is very large, getting a full list could be difficult
  • by chance, this method could result in an unrepresentative sample e.g. too many members of one gender
• opportunity sampling

  the researcher directly asks available members of the target population to take part in the research. This is likely to be individuals the researcher has easy access to and is familiar with.
• how to conduct an opportunity sample?

  1. researcher directly asks any members from within the target population that they have access to, to take part in the research
  2. anyone who agrees is added to the sample until the number of required participants is met
• opportunity sample strengths

  • This method is easy and inexpensive to carry out.
  • fastest way to get a sample for psychological research
• opportunity sample weaknesses

  • The sample may not be representative as it is the type of people that the researcher has easy access to. For research done in universities, this is likely to be young undergraduate students
  • researcher decides who to ask and this could result in researcher bias
• volunteer sampling

  participants offer to take part after finding out about the research but they are NOT DIRECTLY ASKED
• how to conduct a volunteer sample

  1. adverts are put where they are likely to be seen by members of the target population
  2. the advert will include contact details and the researcher will enrol the volunteer into the sample when they are contacted
• volunteer sample strengths

  • Convenient and Easy – It is a quick and simple way to gather participants since researchers just need to advertise their study and wait for volunteers.
  • can reach a very large number of potential participants especially if the site is widely read
• volunteer sample weaknesses

  • Unrepresentative Sample – The sample is likely to be biased because only certain types of people (e.g., highly motivated, with free time) will volunteer, making generalisation difficult.
  • Demand Characteristics – Volunteers may be more eager to please the researcher, increasing the risk of social desirability bias.
• stratified sampling

  when the population is divided into groups (strata) based on characteristics like age, gender, or ethnicity. Participants for the sample are then randomly selected from each group in proportion to how they appear in the overall population.
• how to conduct a stratified sample

  1. Divide into strata – Split the population into relevant subgroups (e.g., 60% female, 40% male).
  2. Calculate proportions – Work out how many participants are needed from each subgroup based on their proportion in the population.
  3. Randomly select participants – Use a random method (e.g., names in a hat or a random number generator) to fairly select participants from each subgroup.
• stratified sample strengths

  • Representative – Ensures key groups are included in correct proportions, improving generalisability.
  • Reduces bias – It avoids the problem of misrepresentation sometimes caused by purely random sampling.
• stratified sampling weaknesses

  • Time-consuming – Sorting people into groups and selecting participants takes longer than other methods.
  • Difficult to categorise – Deciding which characteristics to use for grouping can be tricky, and some people might fit into multiple categories