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Sampling Methods in Research

How to choose who or what to study, and why your choice matters.

7 min read · Written by UK academic writers

Your sample shapes how trustworthy and generalisable your findings are, so examiners expect you to choose and justify it carefully. This guide explains the main sampling methods and when to use them.

Population vs Sample

The population is everyone or everything you are interested in; the sample is the subset you actually study. Good sampling makes the sample represent the population as well as possible.

Probability Sampling

In probability sampling, every member of the population has a known chance of being chosen, which supports generalisation. It is common in quantitative research.

• Simple random: everyone has an equal chance
• Stratified: sample within defined subgroups
• Systematic: select at fixed intervals
• Cluster: sample whole groups

Non-Probability Sampling

Here selection is not random, which limits generalisation but is often practical, especially in qualitative research.

• Convenience: those easiest to access
• Purposive: chosen for specific characteristics
• Snowball: participants recruit others

Sample Size

Quantitative studies usually need larger samples for statistical power, while qualitative studies use smaller samples focused on depth and saturation.

Justify Your Choice

In your methodology, explain why your sampling method and size suit your questions, and acknowledge any limitations they introduce.

Frequently Asked Questions

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