Web Surveys 101

Probability or random sampling survey research methods should always be your first choice when examining your options for data collection.  We recently posted about the basic differences between probability and non-probability sampling methods, here's a bit more depth about the first two probability sampling methods.  Simple random and systematic sampling methods are the basis for stratified and clustered methods.

Simple Random Sampling. Simple random sampling is considered to be the ideal random method because respondents are randomly selected from a list of the entire population.  Every individual has an equal chance of being selected. 

Systematic Sampling. With this method, you select every kth individual or element from the list of the known population.  If you know you need a sample size of 100 to have the required confidence in the survey results, from 3000 members, your kth variable would become 30.  Randomly selecting a number between 1 and 30 would give you your starting point.  When using a systematic sampling method, you always want to start at a random point and begin selecting every kth individual.  Consider how your list is sorted to avoid adding bias to your sample.  If your list is started by factors that could affect responses, such as which state someone lives, you could seriously bias your data. 

These are just two of the probability sampling methods, but it’s important to understand them when looking at clustered and stratified samples.