![]() Or it can be more like the child’s toy sense of model: an actual physical model of something that serves as an aid to thought. It can mean a way of thinking grounded in analogy - electricity as a fluid that flows, an atom as a miniature solar system. Modelling is an old word in science, and the old uses remain. But do politicians and officials understand the limits of what these models can do? Are they all as good, or as bad, as each other? If not, how can we tell which is which? Made digestible, the results affect us all.Īs computer modelling has become essential to more and more areas of science, it has also become at least a partial guide to headline-grabbing policy issues, from flood control and the conserving of fish stocks, to climate change and - heaven help us - the economy. Or it might just incorporate some rough approximations, which are good enough to get by with. It might involve theory, transformed into equations, then computer code. What should we make of this scientific nouvelle cuisine? While it is related to experiment, all the action is in silico - not in the world, or even the lab. Computer simulation, only a few decades old, is transforming scientific projects as mind-bending as plotting the evolution of the cosmos, and as mundane as predicting traffic snarl-ups. Still, the recipe captures crucial features of how most of it has been done for the past few hundred years. Scientific work is vastly diverse and full of fascinating complexities. ![]() If the results fit the predictions, then the theory might describe what’s really going on. Find a plausible theory for how some bits of the world behave, make predictions, test them experimentally. Here’s a simple recipe for doing science.
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