Data and explanations

Overview

This section includes ideas a - e which are about data and the relationship between variables and more abstract ideas f - l, about developing explanations. Students will need these tools when they are evaluating evidence, criticising conclusions from limited data or analysing the introduction of a new theory.

These ideas are the ones that are essential in understanding why we value scientific knowledge and how it differs from some of the explanations involved in alternative medicine or intelligent design.

a, b, c Short practical measurement activities are a good introduction to these ideas. Students will need a qualitative understanding of error bars and confidence intervals. These ideas are important in analysing clinical trials in 9.3 and air quality, 10.3, fuels and the global environment 10.4, and radiation, 10.5.

d, e These ideas relate to the design of experiments. Many examples will overlap with work on 12.3 causal links.

f, g The best examples of these are the historical topics; 9.1 germ theory, 9.7 evolution and 10.6 cosmology. What we mean by models in this context will need elaboration. The atomic model is a familiar one which may be useful here.

h, i, j These three ideas are some of the most important. Experimental testing and re-testing of explanations is the main reason why we trust scientific knowledge. They will be used each time we ask 'what is the evidence?' 'Why do we accept this explanation rather than another?'. Notice though that we do not say that results prove an explanation. They increase our confidence in it.

k Historical examples provide a range of different reasons here including personal commitment to a theory, the status of the scientist promoting the change and the leap of imagination required.

l The history of science is littered with ideas that came to nothing when the work is repeated, cold fusion being one example. The recent fraudulent claims of human clones illustrate another reason for the importance of repeating work. This idea counters the image of science as steady progress as well as emphasising the importance of the scientific community.