Data and interpretation

One of the things that makes scientific research intellectually rewarding and stimulating is the fact that it allows speculation -- hypotheses, really -- about how the experimental observations hang together. Two engaging posts by PhysioProf and Janet Stemwedel frame this aspect of research in terms of "correct" experimental data and their interpretation in "interesting" ways. Here's PhysioProf:

It is essential that one's experiments be "correct" in the sense that performing the same experiment in the same way leads to the same result no matter when the experiment is performed or who performs it. In other words, the data need to be valid.

But it is not at all important that one's interpretation of the data--from the standpoint of posing a hypothesis that is consistent with the data--turns out to be correct or not. All that matters is that the hypothesis that is posed be "interesting", in the sense of pointing the way to further illuminating experiments.

And here's the concluding paragraph of Stemwedel's commentary:

Being wrong about what the data mean is not a crime against science. Being unwilling to test your guesses about what the data might mean, however, is shirking your scientific duties. Since any worthwhile interpretation is going to need to be tested -- by you and by your fellow scientists -- getting a feel for drawing inferences that lend themselves to empirical probing is an important scientific competency. As well, making your peace with having new data blow your interpretation to bits -- then picking yourself up and coming up with a new interpretation to test -- is a valuable life skill.

Both the posts are excellent. Now, go read them!