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# Simple random sampling

Explanations > Social ResearchSampling > Simple random sampling

## Use

Use in simple experiments that require a single sample to be taken from a given population or a representative sample frame.

The people in the sample frame must all be accessible and available.

Use when the target group is sufficiently large. Do not use when the target is a relatively small subgroup that might be missed by this method.

## Method

Create the sample by selecting randomly from the sample frame or population.

This can be done using a paper list of random numbers, although these days a computer is often used.

## Example

A person researching education levels within a company takes the full employee list and applies a random number algorithm to this in order to select people to interview.

## Discussion

The basic principle of simple random sampling is like drawing names out of a hat and is based on the mathematical property that a truly random sample (if big enough) will be representative of the target population.

The simple random sample has two key properties:

1. Unbiased: Each unit has the same chance of being selected.
2. Independent: The selection of each unit is not affected by the selection of other units.

Random number generation is easy these days with a computer where, for example the Excel '=RAND()' function (just type it into any cell) generates a random number between 0 and 1. To generate a number between 0 and 5, multiply this by five and take the integer to round it down (eg. '=INT(5*RAND()').

A problem with random selection is that this is not always possible. For example to do a true random sample of the population of the USA, you would start with a list of everyone there, then select a random sample from this (very big) list, then access those people selected, no matter where they lived and whether or not they wanted to partake in the study.

And the big
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