## Systematic random sampling

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Systematic random sampling uses the same statistical principles as simple random sampling, that is, p values and confidence intervals are calculated the same way. However, systematic random sampling does not involve separate random selection of each household. For this reason, systematic random sampling is often used to select large samples from a long list of households.

Steps in selecting a systematic random sample:

- Calculate the sampling interval (the number of households in the population divided by the number of households needed for the sample)
- Select a random start between 1 and sampling interval
- Repeatedly add sampling interval to select subsequent households

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

We first calculate the sampling interval by dividing the total number of households in the population (40) by the number we want in the sample (10). In this case, the sampling is 4. We then select a number between 1 and the sampling interval from the random number table (in this case 3). Household #3 is the first household. We then count down the list starting with household #3 and select each 4^{th} household. For example, the second selected household is 3 + 4, or #7. Note that when you reach the end of the list, you should have selected your desired number of households. If you have not, you have counted wrong or miscalculated the sampling interval. You should go back and start over.

This is what your final selection should look like:

Systematic random sampling can be done with any list.

Systematic random sampling can also done without a list. If the actual sampling units, such as houses or shelters, are arranged in order, you can count down the units in the field. Just calculate the sampling interval, choose a random number between 1 and the sampling interval, then start counting the units from one end of the population.