Sampling 101

There are two types of sampling methods, these are; probability sampling also known as random sampling, and non-probability sampling (Kothari, 2004). Jackson (2011) describes probability sampling as a method where each member of the population has a known probability of selection to be part of the sample. 

In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. Researchers rarely survey the entire population because the cost of a census is too high. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller, it is possible to ensure homogeneity and to improve the accuracy and quality of the data (Babbie 2001). Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly stratified sampling (blocking). Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population (Black, 1999).

When the set of all possible items in a population is very large it may be too costly or time consuming to do a comprehensive analysis of all of the items. For example, during a survey, there isn’t enough time or resources to talk to every participant of the survey, witness every process step or look at every quality record. If the customer base is large, it may be too costly to survey all the customers to determine their satisfaction level. Evaluating or estimating attributes or characteristics of the entire system, process, product or project through a representative sample can be more efficient while still providing the required information. To legitimately be able to use a sample to extrapolate the results to the whole population requires the use of either probabilistic or non-probabilistic sampling methods, (Babbie 2001).