Sampling

Sampling - The Basics

Choosing a Sampling Approach

There are two main types of samples - probability and non-probability. The main sampling difference for each methodology (qualitative and quantitative) is based primarily on the purpose of the research. If the purpose is to deductively “test” a specific hypothesis then a random sample that is sufficiently large to represent the population is the desired sampling approach. That way the findings can be generalized to that larger population. On the other end of the spectrum is an exploratory qualitative study with a purpose of “building” a theory. Qualitative inductive theory building studies worry less about representative samples and more about getting the right people to provide a rich data set - often called a “purposive” sample. Of course there are many variations to these approaches including sampling for mixed methods studies. In the end, when practical you want to work toward a representative sample but unless you are expanding the theory to increase generalizability to other populations or testing a theory a purposive sample might be more appropriate.

Representative (a.k.a. Probability)

Used primarily for theory testing, quantitative studies. A representative sample has to meet two requirements: (a) it has to be random and (b) it has to be large enough for the desired significance level.

Random Selection - Simply means that each potential participant in the sampling frame has an equal chance of being chosen.

Sample Size - Many research methods texts and online sources will offer “rules of thumb” for determining sample size. I recommend that you ignore all of these and instead use a formula or an online calculator that uses a formula to determine the appropriate sample size based on the size of the sampling frame and the desired confidence level. Example online sample size calculator.

If either if these requirements is not met the sample is not representative of the population or sampling frame.

Non-Representative (a.k.a. Non-Probability)

Used primarily for qualitative, theory building studies. First, it is usually impractical to include a sample size large enough to be representative when using time consuming research methods related to qualitative research such as interviews and so forth. Second, random participant selection is often not desirable. Many theory building qualitative studies need data from participants with specific knowledge and experience. Thus a purposive sample.

Purposive Sample - A purposive sample is one where participants are selected that meet particular criteria in order to achieve a particular purpose. They may have specific knowledge (e.g., engineers), a particular perspective (e.g., CEO), experienced a specific event (e.g., downsizing) or a combination of characteristics. This is the most common sampling approach for theory building qualitative studies focused on business, organizations and management.

I recommend that you never ever use a convenience sample. It is a waste of time for you and the participants. Ask yourself a question: If a Gallup public opinion survey used a convenience sample (i.e. without probability concepts), would you believe their findings? In your own dissertation, if you use a convenience sample will anyone believe your results or have the confidence to act on your conclusions?