20.1: Science

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The key feature of genuine science it that its claims are testable, in one way or another, but various other factors also play a central role. No simple account can do justice to every aspect of every scientific field, but we will examine several features that are central to most of them. These include:

Formulating theories or hypotheses (often about causation)
Making predictions
Testing
Getting data (sampling)
Drawing inferences from sample to population
Assessing covariation (correlation)
Explanation

Some items on this list are more important in some sciences than in others, but much science involves some version of most of them.

We have studied several of these topics in earlier chapters, but it is worth revisiting them in the context of scientific investigation. It might be helpful to think of the above list as something of a flowchart, in which one moves through the steps numerically, but you should also keep in mind that in the things can be trickier in the real world. While the best place to start is by formulating a hypothesis, we sometimes just don’t know enough about an issue to do this, and instead we must start with data collection. In the context of medical research, we call this a study in nature. Researchers who are not yet at a point where they are prepared to test a product or procedure will observe subjects suffering from a disease or condition to try to infer causes or potential solutions (so skipping to steps 4 & 5 above). Only then are they able to develop a hypothesis, make a prediction, etc.