## Simple random sampling

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Simple random sampling is the most intuitive sampling approach. If every household in the population has some unique identifier, such as a number or the name of the head of the household, and you know how many households you want to include in the survey sample, then you could simply write this identifier for each household on a separate piece of paper, put all the pieces of paper in a bag, shake well, and draw as many from the bag as you need to achieve your intended sample size. This is simple random sampling.

Simple random sampling:

- Involves selection of households which is independent and random
- Is the basis for most statistical theory, that is:
- The most common methods to calculate p values and confidence limits
- The output from most statistics computer programmes assume simple random sampling

Regardless of what form your data are in, the important characteristic of simple random sampling is that the person doing the selecting has NO CONTROL over which households are selected. The selection is entirely random, and the selection of each household is not dependent on the selection of other households.

__Example of simple random sampling of 10 households from a list of 40 households__

We have a list of 40 heads of households. Each has a unique number, 1 through 40. We want to select 10 households randomly from this list. Using a random number table, we select consecutive 2-digit numbers starting from the upper left. If a random number matches a household's number, that household is added to the list of selected households. If a random number does not match a household's number (for example, if it is greater than 40), then it does not select a household. After each random number is used, it is crossed out so that it is never used again. We continue to select households until we have 10.

Note that even though the selected households appear somewhat clustered, if the random number table is truly random, the selected households have been randomly selected.