When drawing a survey population that you want to use to extend knowledge to the total population you need to sample in a way that doesn't introduce bias. The S

When drawing a survey population that you want to use to extend knowledge to the total population you need to sample in a way that doesn't introduce bias. The Simple Random Sampling method is the gold standard here: sample in a way such that each subset of the total population of a given size has equal chance of being selected. This includes, as a special case, that each individual has an equal chance of being selected. http://en.wikipedia.org/wiki/Simple_random_sample http://en.wikipedia.org/wiki/Simple_random_sample More complex sampling methods can be used since SRS is usually intractable (you'd need to put every single person in your superpopulation into a lottery by magic, else you'll bias toward those who like email surveys or actually read their mail). In the event you use one of these you usually need a bias mitigation strategy. For instance, you might just state something like "we assume that receptiveness to email and dislike for Java are correlated". It's then up to the reader to decide whether they trust your assumptions. You might also do some other support studies which help to measure the size of the bias your non-SRS sampling methodology induces and then correct for them.