# Data collection - Sampling techniques

• Created by: KGR01
• Created on: 16-05-18 21:12
Simple random sampling
Every possible sample of a given size is equally likely to be selected.
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Stratified sampling
Sub-groups called strata are used to identify different groups that are likely to have different voting patterns. In stratified sampling, you would ensure that a random sample is taken from every strata.
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Cluster sampling
Random samples are taken from selected strata (also called clusters).
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Systematic sampling
Individuals are chosen from a sampling frame (e.g. if you were surveying telephone subscribers you might sample the 10th name on each page of the directory).
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Quota sampling
An interviewer's quota is usually specified in stratified terms (e.g. how many males/females). The choice of who is sampled is then left up to the interviewer and so is definitely non-random.
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Opportunity sampling
When circumstances make a sample readily available (e.g. the representatives at a conference of hospital doctors are used as a sample to investigate the opinions of hospital doctors in general on a particular issue).
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Self-selecting sample
When those involved volunteer to take part, or are given the choice to participate or decline (e.g. online surveys).
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## Other cards in this set

### Card 2

#### Front

Sub-groups called strata are used to identify different groups that are likely to have different voting patterns. In stratified sampling, you would ensure that a random sample is taken from every strata.

#### Back

Stratified sampling

### Card 3

#### Front

Random samples are taken from selected strata (also called clusters).

### Card 4

#### Front

Individuals are chosen from a sampling frame (e.g. if you were surveying telephone subscribers you might sample the 10th name on each page of the directory).

### Card 5

#### Front

An interviewer's quota is usually specified in stratified terms (e.g. how many males/females). The choice of who is sampled is then left up to the interviewer and so is definitely non-random.