This week I have decided to post a short summary of what I found most interesting about sampling. Like most topics in this course, I had underestimated the complexity of sampling. It seemed so simple ... grab some random people and off you go! Wrong... One aspect of sampling that I found most interesting came from the Luker reading for this past week (Ch. 6 p. 100). That is, undertaking a huge (think national) sample is very expensive. As we know from our SSHRC proposals, research is highly dependent upon grants. Therefore money is often limited. I thought it was interesting that many projects choose to use already existing data on populations. By doing this, the research is forced to take on whatever bias accompanies a specific organization's data. Luker gives a great example of a survey which was so outdated it had only three options for race: white, black and other. I will not be conducting research on this scale, but I think it is some food for thought. Choosing to use an organization's existing data would be a very difficult decision, because it will set the foundation for the rest of your research and could make or break your project. Will this bring into question the validity of your results or the neutrality of your position as a researcher?