Sampling

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Sampling Revision

Sampling

Sampling is a technique where instead of taking data from the whole population, we take data from a small percentage of the population. This can be then used to make conclusions on the whole population.

Random Sampling

Sampling is a useful technique when you need information from a large population. It is not efficient and sometimes impossible to take data from every single organism in a population, and so sampling is a useful approach.

It is vital that sampling is random. The data from the sample will be used to make conclusions about the overall population, so the sample cannot have any bias.

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Sampling an Area

Sometimes you might need to sample parts of an area, rather than looking at the entire thing. For example, you might want to look at the population size of daisies in a field.

The most fair and non-biased way to do this is to grid out your area into smaller segments. Label these segments and use a random number generator to generate coordinates, from which you will take your samples.

More information about using quadrats and transects in sampling can be found here.

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Sampling a Population

Say you wanted to find out some information about the population of your town, perhaps what shoe size they are. It would be inefficient and time-consuming to ask every single person in the UK what shoe size they are. Therefore we could pick a smaller sample size of this population, and ask them.

It is again vital that this sampling is completely random, to ensure there is no bias when selecting the sample. 

Sampling is often used for healthcare purposes, like research into genetic diseases for example. It can also be used to select people for drug testing. More information about drug testing can be found here.

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Sampling Example Questions

A sample must be random because this eliminates any bias.

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The area should be gridded out with coordinates, and then a random number generator should be used to make some coordinates for the samples.

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The samples are all close to each other.

This might be because the student hasn’t used a random number generator.

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