There are two basic types of sampling - probability and nonprobability samples. They differ on two key characteristics. First is the issue of whether sampling error can be estimated. Nonprobability samples do not allow sampling error to be estimated. Thus, it is not possible to determine the accuracy, within a given confidence interval, of our measures.
Probability samples do permit sampling error to be measured.
In addition, the process of random selection leads, on average, to a representative sample. By randomly selecting people into our sample, we can control on unknown characteristics. That is, we don't have to know the age of the members of our sampling frame in order to select a sample representative of all age ranges - this occurs naturally through the random selection process. But, we can only build such representation in a nonprobability sample from such known characteristics. Snowball Sampling 8.