Introduction to Sampling
In Psychology, researchers rarely have the time or money to study every single person in the world. Instead, they select a smaller group of people to represent the larger group they are interested in. This process is called sampling. Understanding how we choose these participants is vital because it determines whether the results of a study can be applied to people in real life!
Quick Review: To understand sampling, you need to know two key terms:
1. Target Population: The entire group of people the researcher wants to study (e.g., "all teenagers in the UK" or "all people with a phobia of buttons").
2. Sample: The actual group of people who take part in the research study.
The "Big Three" Sampling Techniques
The Cambridge 9990 syllabus focuses on three main ways to get a sample. Don't worry if these seem similar at first; we will break down the differences clearly.
1. Opportunity Sampling
This is when a researcher recruits people who are available at the time and fit the criteria. It is the "easiest" way to find participants.
Example: Standing in a university hallway and asking the first 20 students who walk past to fill out a survey.
Strengths:
- Quick and Easy: It is the fastest and cheapest way to get a sample because you use whoever is there.
- Less Planning: You don't need a pre-made list of every person in the population.
Weaknesses:
- Biased: The sample might not represent the whole population. For example, if you sample at a university at 9:00 AM, you only get people who are awake and on campus early!
- Generalisability: Because the sample is biased, it is harder to say the results apply to everyone else.
2. Volunteer (Self-Selecting) Sampling
This is when participants choose to take part in the study. Usually, the researcher puts up an advertisement, a social media post, or an email invite, and waits for people to respond.
Example: Milgram (1963) used a newspaper advertisement to find men for his study on obedience.
Strengths:
- Willing Participants: People who volunteer are usually highly motivated. They are less likely to "drop out" (attrition) because they wanted to be there in the first place.
- Easy to reach specific groups: If you need people with a rare hobby, an ad in a specific magazine will find them easily.
Weaknesses:
- Volunteer Bias: People who volunteer for studies might be different from those who don't. They might be more helpful, more social, or have more free time. This makes the sample unrepresentative.
- Demand Characteristics: Volunteers might try harder to guess the aim of the study and change their behavior to "help" the researcher.
3. Random Sampling
In a random sample, every person in the target population has an equal chance of being chosen. This usually requires a list of everyone in the population (a "sampling frame") and then using a computer or a hat to pick names.
Example: Putting the names of every student in a school into a hat and pulling out 30 names.
Strengths:
- Most Representative: It is the "gold standard" because it avoids researcher bias. The researcher cannot choose "friendly-looking" people.
- High Generalisability: Because the sample is likely to include a mix of different types of people, the results are more likely to apply to the whole population.
Weaknesses:
- Difficult and Time-Consuming: It is very hard to get a list of every single person in a large population (like "all people in London").
- Refusal: Even if you pick someone randomly, they might say "no," which can turn your random sample back into a volunteer sample!
Comparison Summary Table
Use this table for a quick revision of the techniques.
Technique: Opportunity
How it works: Ask whoever is there.
Effort: Low.
Bias: High (Researcher picks people).
Technique: Volunteer
How it works: People come to you.
Effort: Medium.
Bias: High (Participants are "special" types).
Technique: Random
How it works: Equal chance for everyone.
Effort: High.
Bias: Low (Mathematical chance).
Sampling in the Core Studies
To do well in Paper 1 and Paper 2, you should link these techniques to the studies you have learned. Here are two famous examples:
1. Piliavin et al. (Subway Samaritans): This used opportunity sampling. The participants were simply the people who happened to be on the New York subway train at the time of the study.
2. Milgram (Obedience): This used volunteer sampling. He placed an advertisement in a newspaper and paid participants \( \$4.50 \) for their time.
Key Concept: Generalisability
In your exams, you will often be asked to evaluate a sample. The most important word to use is generalisability. This refers to how well the findings of a study can be applied to the target population.
A sample has low generalisability if:
- It is too small (e.g., only 5 people).
- It is ethnocentric (all from one culture).
- It is androcentric (all males) or gynocentric (all females).
- The sampling technique was biased (like opportunity sampling).
Common Mistakes to Avoid
The "Random" Confusion: Many students say, "The researcher randomly asked people in the street." This is incorrect! Asking people in the street is Opportunity Sampling. For it to be Random Sampling, the researcher must have a list of every person and use a random method (like a computer) to pick them.
Generalisability vs. Reliability: Don't mix these up! Sampling is usually about validity and generalisability (does the sample represent the group?). Reliability is about whether the procedure can be repeated to get the same results. (Note: Cross-reference the "Validity and Reliability" chapter for more on this.)
Quick Review Quiz
1. Which sampling technique involves putting up a poster in a gym? (Answer: Volunteer)
2. Which technique is most likely to be representative of the whole population? (Answer: Random)
3. What is the main weakness of opportunity sampling? (Answer: It is biased and may not be generalisable)
4. If a researcher uses a computer to pick 50 names from a school register, what technique is this? (Answer: Random)
Key Takeaway: Choosing a sample is a balance between practicality (how easy it is) and representativeness (how fair it is). Random sampling is the most "fair," but opportunity and volunteer sampling are often more "practical" for busy psychologists!