Apr 07 2009
From Data to Conclusion: A Non-Concrete Link
There is an important difference between the data science generates and the explanations and conclusions it draws. I view these as the two arms of science: the empirical arm and the philosophical arm. One is all about numbers and measurement, the other about arguments and reasoning.
Strong science is careful and sober in its explanation of data. Jumping to over-confident and/or far-reaching conclusions from a limited amount of data, or from poor quality data, is not strong science.
The critical thinker, I believe, should be able to identify the difference between data and explanation. Consider this finding from a study on the perceptual ability of a species of birds. Can you identify which sentence is more data (empirical), which more explanation (philosophical)?
Jackdaws seem to recognize the eye’s role in visual perception, or at the very least they are extremely sensitive to the way that human eyes are oriented.
When presented with a preferred food, hand-raised jackdaws took significantly longer to retrieve the reward when a person was directing his eyes towards the food than when he was looking away.
As you probably guessed, the second is the data. It has the details, the all-important nitty-gritty of how the data was generated. The first is more explanation. And there is a difference. Sometimes the explanation doesn’t venture far from the data. It takes few liberties. Other times it does. And critical thinkers will notice this.
