sampling

• volunteer sample- where pps pick themselves through newspaper adverts, noticeboards or online,
• opportunity sampling- convenience sampling, uses people who are available at the time the study is carried out and willing to take part, based on convenience,
• random sampling- when every person in the target population has an equal chance of being selected, an example of random sampling would be picking names out of a hat
• systematic sampling- when a system is used to select participants, picking every nth person from all possible participants, N- the possible number of people needed for the sample
• stratified sampling- when you identify the subgroups and select pps in proportion to their occurrences
• snowball sampling- when researchers find a few participants, and then ask them to find pps themselves and so on
• Quota sampling- when researchers will be told to ensure the sample fits certain quotas, eg they might be told to find 90 participants, with 30 of them being unemployed
• random sampling- each member of the target population has a mathematically equal chance of being in the experiment's sample
• methods of random sampling- drawing names out of a hat and laying them out until a full sample size is complete, or by putting all names into a computer software and using AI to randomly draw participants through code till you have a full sample size
• a strength of random sampling- removes researcher bias as the researcher cannot choose the participants that they want to form the sample, avoiding the possibility the researcher picks pps they feel are to give a preferred result
• example of how someone could systematically sample pps- pps are chosen from a list of a target population, each nth pp is chosen to form the sample eg (every 5th, 10th, or 100th name on the list)
• Random sampling drawback- there is still a chance that you could gather an un-representative sample from this method, for example too few members of one gender or with no members of a minority group, if the target population is very large getting a full list could be difficult
• opportunity sampling- the fastest way to sample for psychological research, reducing the time it takes to conduct research and likely reducing the cost involved compared to more complex methods of sampling
• opportunity sampling- unlikely to be representative of a population as pps chosen are people who the researcher has early access to, eg in undergraduate universities, the sample will consist mainly of young university students,
• how volunteer sampling is conducted- ads are placed where they are likely to be seen by members of a target population (eg the gym for fitness enthusiasts or the pub for alcoholics), the advert will include contact details and the researcher will enrol the volunteer into the sample when they are contacted by the volunteer.
• issues with volunteer sampling- the types of people who volunteer to take part in these studies are likely to have different characteristics to the target population, they are likely to be friendlier and have more free time available- volunteer bias
• stratified sampling- by selecting from within strata, the characteristics of participants within the sample are in the same proportion as found within the target population.
• How to conduct a stratified sample- strata/subgroups are identified along with their proportion in the target population (eg gender, ethnicity, education level), random sampling is then used to select the number of participants required from within each stratum
• positives of statified sampling- representative of the larger target population, meaning the results found within the sample should be generalisable to the target population, as the participants are randomly chosen from within each stratum this means it avoids researcher bias