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examBoard: AQA
examType: GCSE
lessonTitle: Review and Practice - Sampling
When psychologists conduct research, they usually can't study everyone in a population. Instead, they select a smaller group (a sample) to represent the larger group. The way researchers choose this sample is called the sampling method and it's super important for making sure research findings are reliable and valid.
Key Definitions:
Random sampling gives everyone in the population an equal chance of being selected. It's like putting everyone's name in a hat and picking out names without looking.
How to do it: Number everyone in the population, then use a random number generator to select participants.
Strengths: Reduces bias, creates representative samples, findings can be generalised.
Limitations: Needs a complete sampling frame, can be time-consuming, may not include enough people from smaller groups.
Systematic sampling involves selecting participants at regular intervals from a list.
How to do it: Calculate a sampling interval (population size ÷ desired sample size), randomly select a starting point, then select every nth person.
Strengths: Simple to use, spreads the sample across the population, more convenient than random sampling.
Limitations: Can create bias if there's a pattern in the list that matches the sampling interval.
Stratified sampling divides the population into subgroups (strata) based on characteristics like age or gender, then takes samples from each group.
How to do it: Identify important subgroups, determine what percentage of the population each subgroup represents, then select that same percentage for your sample.
Strengths: Ensures all subgroups are represented proportionally, reduces sampling error.
Limitations: Requires knowledge of population characteristics, more complex to organise.
Opportunity sampling (also called convenience sampling) involves selecting whoever is available and willing to participate.
How to do it: Ask people who are easy to access (e.g., people walking by, friends, students).
Strengths: Quick, easy and cheap to do.
Limitations: Highly biased, not representative, limited generalisability.
Snowball sampling starts with a few participants who then recruit others they know and so on.
How to do it: Find a few participants who match your criteria, then ask them to suggest others who might participate.
Strengths: Good for hard-to-reach populations, helps access hidden groups.
Limitations: Sample likely to share similar characteristics, not representative.
Volunteer sampling involves participants choosing to take part in the research themselves.
How to do it: Advertise the study and wait for people to volunteer.
Strengths: Easy to gather participants, participants are usually motivated.
Limitations: Self-selection bias (volunteers may differ from non-volunteers), not representative.
The sampling method you choose depends on several factors:
Random, systematic and stratified sampling are probability methods. Use these when:
Opportunity, snowball and volunteer sampling are non-probability methods. Use these when:
For the most reliable research:
Stanley Milgram's famous obedience study used newspaper advertisements to recruit male participants aged 20-50 from New Haven, Connecticut. This was a volunteer sample.
Sampling limitations: The sample wasn't representative of the general population as it only included men from one area who were willing to volunteer. This limits how much we can generalise the findings to other groups.
Impact: Despite sampling limitations, the study revealed important insights about human obedience to authority. However, modern replications with more diverse samples have found varying levels of obedience across different cultures and contexts.
When you're reading about psychological studies, it's important to critically evaluate the sampling method used. Ask yourself:
Sampling bias occurs when some members of the population are more likely to be included in the sample than others. This can happen when:
The size of your sample matters:
Let's look at how to apply different sampling methods to a research scenario:
Imagine you want to study how social media affects teenagers' mental health in the UK.
Random sampling approach: Get a list of all UK teenagers (sampling frame), number them and use a random number generator to select participants.
Stratified sampling approach: Divide teenagers into groups based on age, gender and socioeconomic status, then randomly sample from each group proportionally.
Opportunity sampling approach: Ask teenagers at your local school to participate.
Best choice? Stratified sampling would likely give the most representative results, ensuring different age groups, genders and backgrounds are included proportionally.
Remember: The sampling method you choose will directly affect how valid and reliable your research findings are. Always consider your research aims, available resources and the importance of generalisability when selecting a sampling method.
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