Sampling in Psychological Research
1. Meaning and Concept of Sampling
In psychological research, it is usually impossible to study every individual belonging to a population. Therefore, researchers select a sample, which is a smaller, manageable group drawn from the population. This process of selection is known as sampling.
flowchart TD A[Target Population] --> B[Sample Selection] B --> C[Data Collection] C --> D[Inference about Population]
2. Probability and Non-Probability Sampling
Sampling techniques are broadly classified into probability and non-probability methods, depending on whether every unit has a known chance of selection.
flowchart TD S[Sampling Methods] S --> P[Probability Sampling] S --> N[Non-Probability Sampling]
3. Probability Sampling Methods
3.1 Simple Random Sampling
In simple random sampling, each individual in the population has an equal and independent chance of being selected. Selection may be done through random number tables or computer-generated lists.
Early learning and memory experiments ensured random selection of participants to avoid systematic bias in cognitive performance.
Why it is valued
- Reduces selection bias
- Allows strong statistical generalisation
Limitations
- Requires complete population list
- Difficult in large or scattered populations
flowchart LR P[Population List] --> R[Random Selection] R --> S[Sample]
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3.2 Stratified Sampling
In stratified sampling, the population is divided into homogeneous subgroups (strata) such as gender, age, or socioeconomic status. Samples are then drawn proportionately from each stratum.
National mental health surveys stratify samples by rural-urban residence and gender to ensure balanced representation.
Why psychologists use it
- Ensures inclusion of minority groups
- Improves accuracy of comparisons
flowchart TD P[Population] P --> S1[Stratum A] P --> S2[Stratum B] S1 --> SA[Sample] S2 --> SB[Sample]
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3.3 Systematic Sampling
Systematic sampling involves selecting every nth unit from an ordered list after a random starting point. It is often used in institutional and field settings.
Selecting every 5th patient entering a hospital OPD to study stress or anxiety patterns.
Strength
- Simple and time-efficient
Risk
- Hidden periodicity in population list may bias results
4. Non-Probability Sampling Methods
4.1 Convenience Sampling
Convenience sampling selects participants who are easily available to the researcher. It is common in laboratory and classroom research.
Many classic cognitive psychology studies relied on college students, leading to the “WEIRD population” critique.
Advantage
- Fast and economical
Limitation
- Low external validity
4.2 Purposive Sampling
In purposive sampling, participants are selected because they possess specific characteristics relevant to the study.
Selecting individuals diagnosed with PTSD to understand trauma-related coping mechanisms.
flowchart TD P[Population] P --> C[Specific Criterion] C --> S[Selected Sample]
4.3 Snowball Sampling
Snowball sampling relies on participants to refer other participants. It is especially useful for studying hidden or stigmatized groups.
Psychological research on substance abuse, domestic violence survivors, or underground communities.
flowchart LR A[Participant 1] --> B[Participant 2] B --> C[Participant 3] C --> D[Participant 4]
5. Choosing the Right Sampling Method
| Research Situation | Preferred Sampling | Reason |
|---|---|---|
| Controlled experiments | Random sampling | Minimises bias |
| Large population surveys | Stratified sampling | Ensures representation |
| Clinical case studies | Purposive sampling | Focus on specific traits |
| Hidden populations | Snowball sampling | Access through referrals |
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