Sampling methods

  • Created by: jaaaz_v
  • Created on: 14-06-15 18:01

Random sampling

Random samples give each member of the target population a fair chance of being represented. You could take a random sample by picking names out of a hat :)

An advantage of random sampling is that all members of the target population have a fair chance of being selected.

A disadvantage of this sampling method is that the sample that chosen may not be representative of the qualities of the target population.

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Systematic sampling

This is when the sample is picked by selecting people from a list at intervals. Eg. Every fifth person in a list being chosen.

An advantage of this is that there's no bias in the selection of participants.

A disadvantage is that there may be a hidden pattern in the list which would affect the sample that's chosen.

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Stratified sampling

Where the data is selected in proportion to the qualities of the whole population.

An advantage of this method of sampling is that its representative of the target population.

A disadvantage of this method is that it can be time consuming and expensive.

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Convenience sampling

This is when the first so many pieces of data in a list are sampled (eg. picking the first 50 pieces of data.

This sampling method is quick, however the data thats selected isn't normally representative of the population)

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Cluster sampling

When the population is divided into groups (clusters) and then a group is chosen at random.

An advantage of this is that it makes the selection of data simple and theres no bias in the selection of data (because its random). A disadvantage is that the groups may not be representative of the population,

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When all of the data in the population is taken. A census of the whole of the UK is taken every ten years.

An advantage of this is that its unbiased.

However, it is very time consuming, can be expensive, and difficult.

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