Sample and population in research

In psychological research, it's often impossible to study every individual who might be relevant to a question. This leads researchers to select a smaller group for testing, while aiming to apply their findings more broadly.

Population and sample

• Population - This refers to the entire group of individuals that the researcher is interested in studying, such as all adults with anxiety or all students in a school.
• Sample - This is a smaller subset of the population that is actually tested in the study. The sample is chosen to represent the population, allowing researchers to draw conclusions without examining everyone.

Researchers select a sample because testing an entire population would be too time-consuming, expensive, or impractical. The goal is for findings from the sample to be generalisable - meaning they can be applied to the wider population with reasonable accuracy.

Importance of generalisability

Generalisability is crucial for the value of research. When evaluating a study's generalisability, consider the sample tested and how participants were selected.

Opportunity sampling technique

Opportunity sampling is a common method where researchers select participants who are readily available at the time and place of the study. This approach relies on convenience, such as approaching people in a public space or using those already present in a setting like a classroom.

Strengths of opportunity sampling

• It allows researchers to gather a large sample quickly, as no complex planning is needed for selection.
• This method requires minimal effort and resources, making it practical for studies with time constraints.

Weaknesses of opportunity sampling

• The sample may not be representative of the population, as researchers might unconsciously choose people who seem approachable or suitable, introducing bias.

Link to a psychological study: Hölzel et al.

• Aim - Hölzel et al. investigated changes in brain structure related to mindfulness practice.
• Participants - The researchers used an opportunity sample of 35 right-handed, healthy adults recruited from three Mindfulness-Based Stress Reduction (MBSR) courses at the Centre for Mindfulness.
• Method - Participants underwent brain scans before and after an eight-week MBSR programme to examine grey matter density.
• Evaluation - This sampling was quick but may have biased the sample towards people already interested in mindfulness, limiting generalisability to the broader population.

Random sampling technique

Random sampling involves selecting participants in a way that gives every member of the population an equal chance of being chosen. This is often done using methods like drawing names from a list or using a random number generator.

How random sampling works

1. Identify the entire population, such as listing all members of a group.
2. Assign each member a number or identifier.
3. Use a random process, like picking names from a hat or computer-generated selection, to choose the required number of participants.

This method aims to create a sample that mirrors the population's diversity, as no personal bias influences who is selected.

Strengths of random sampling

• It is more likely to produce a representative sample, enhancing the generalisability of findings.
• By eliminating researcher bias, it increases the study's validity.

Weaknesses of random sampling

• It can be time-consuming and resource-intensive to create a complete list of the population and perform the random selection.
• Some selected individuals may decline to participate, requiring replacements, which could introduce subtle biases if not handled carefully.

Volunteer sampling technique

Volunteer sampling, also known as self-selecting sampling, occurs when researchers advertise for participants and allow people to choose whether to take part. This might involve placing adverts in newspapers, online, or on noticeboards, targeting those with specific traits or experiences.

Strengths of volunteer sampling

• It is effective for recruiting participants with particular characteristics, such as rare experiences or conditions, that might be hard to find otherwise.
• Volunteers are often motivated, which can lead to higher engagement in the study.

Weaknesses of volunteer sampling

• Not everyone may see or respond to the advert, potentially resulting in a small or unrepresentative sample.
• Those who volunteer might differ from non-volunteers in traits like extroversion or helpfulness, creating a biased sample that limits generalisability.

Link to a psychological study: Milgram

• Aim - Milgram conducted a famous experiment on obedience to authority.
• Participants - He recruited a volunteer sample by placing a newspaper advertisement in the New Haven district, seeking people for a study on learning and memory.
• Method - Volunteers responded to the advert and participated in tasks where they believed they were administering electric shocks to a learner, testing obedience levels.
• Evaluation - This method attracted a specific type of person willing to volunteer, which may not represent the wider population, potentially affecting how far the findings on obedience can be generalised.