Sample surveys involve the selection and study of a sample of items from a population. A sample is just a set of members chosen from a population, but not the whole population. A survey of a whole population is called a census.
A sample from a population may not give accurate results but it helps in decision making.
Examples of sample surveys:
- Phoning the fifth person on every page of the local phonebook and asking them how long they have lived in the area. (Systematic Sample)
- Dropping a quad. in five different places on a field and counting the number of wild flowers inside the quad. (Cluster Sample)
- Selecting sub-populations in proportion to their incidence in the overall population. For instance, a researcher may have reason to select a sample consisting 30% females and 70% males in a population with those same gender proportions. (Stratified Sample)
- Selecting several cities in a country, several neighbourhoods in those cities and several streets in those neighbourhoods to recruit participants for a survey. (Multi-stage sample)
The term random sample is used for a sample in which every item in the population is equally likely to be selected.
While sampling is a more cost effective method of determining a result, small samples or samples that depend on a certain selection method will result in a bias within the results.
The following are common sources of bias:
- Sampling bias or statistical bias, where some individuals are more likely to be selected than others (such as if you give equal chance of cities being selected rather than weighting them by size)
- Systemic bias, where external influences try to affect the outcome (e.g. funding organizations wanting to have a specific result)