Suppose your population is all site traffic for a particular month. If you have a steady stream of 25,000 users a month and you want a sample of 500 users, then you give each person a 1 in 50 chance of getting the survey. Or you can use systematic random sampling. A convenience sample is a group of people selected because selecting them is easy. A convenience sample might be the first 100 people to visit a site, a group of employees, or paid respondents.
Convenience samples are often unrepresentative for reasons unforeseen by researchers.
Research based on convenience samples can be used as a launching pad for identifying issues, but extrapolation based on convenience samples can be dangerous. We have just scratched the surface of sampling, but I hope I've opened your eyes to the implications of how the type of sampling you choose can affect your results. Next time we will cover the actual process of designing surveys and other media for customer feedback. Michael Hochster received his Ph.D. in statistics from Stanford University and a B.A. in mathematics with high distinction from the University of California at Berkeley, where he was elected to Phi Beta Kappa in his junior year. Before joining cPulse , Michael worked as an applied statistician in the drug discovery group at Schering-Plough Research Institute.