First, it is usually too costly to test the entire population..The second reason to sample is that it may be impossible to test the entire population.The third reason to sample is that testing the entire population often produces error. Thus, sampling may be more accurate. Perhaps an example will help clarify this point. The final reason to sample is that testing may be destructive. It makes no sense to lesion the lateral hypothalamus of all rats to determine if it has an effect on food intake. We can get that information from operating on a small sample of rats. Also, you probably would not want to buy a car that had the door slammed five hundred thousand time or had been crash tested.
The first sampling procedure is convenience. Another form of sampling is the simple random sample. A systematic sample is conducted by randomly selecting a first case on a list of the population and then proceeding every Nth case until your sample is selected. This is particularly useful if your list of the population is long. Stratified sampling makes up the fourth sampling strategy. In a stratified sample, we sample either proportionately or equally to represent various strata or subpopulations. Cluster sampling makes up the final sampling procedure. In cluster sampling we take a random sample of strata and then survey every member of the group.