Originally Posted by
Replicon
I totally get that they're aware of these factors, and do their best to come up with elegant experiments, but even in your hypothetical examples, there are unknowns creeping in, that you can't just mitigate easily. If you're interested in the number of reasons they give, you're likely trying to correlate the number of reasons ("rationalization factor?" hehe) to something specific. However, a variance in numbers of reasons given might be more highly affected by another, unanticipated factor. It's probably true that with a big enough sample size, and good enough randomization, a correlation would be meaningful. In other words, if you're isolating two groups of people that are random, except for one attribute you want to measure, there is a size where the attribute split will overwhelm other random factors that could affect the results. But since there's no good way to know, statistically, how big of a sample you need to have any kind of expectations about the result (since, among other reasons, you don't actually know just how strong a correlation to expect), any experiment conducted by a master's student on a relatively small number of people (in the tens or hundreds), I would think, has a reliability issue to be dealt with.