Science and Technology

Science encompasses the systematic study of the structure and behaviour of the physical and natural world through observation and experiment, and technology is the application of scientific knowledge for practical purposes. Oxford Reference provides more than 210,000 concise definitions and in-depth, specialist encyclopedic entries on the wide range of subjects within these broad disciplines.

Our coverage comprises authoritative, highly accessible information on the very latest terminology, concepts, theories, techniques, people, and organizations relating to all areas of science and technology—from astronomy, engineering, physics, computer science, and mathematics, to life and earth sciences, chemistry, environmental science, biology, and psychology. Written by trusted experts for researchers at every level, entries are complemented by illustrative line drawings, equations, and charts wherever useful.

What is the one term or concept that everyone—from students to everyday web users—should be familiar with? Why?

I wish that everyone understood the scientific method, and in particular the unique importance of the controlled experiment as a method of scientific discovery. Children should be taught at school what an experiment is and why it is such a powerful way of discovering the truth. Psychology uses various research methods, but the most powerful is undoubtedly controlled experimentation, not because it is more objective or precise than other methods, but because it is uniquely capable of providing evidence of causal effects.

The defining features of an experiment are manipulation of a conjectured causal factor, called an independent variable because it is manipulated independently of other variables, and examination of the effect of this on a dependent variable, while simultaneously controlling all other extraneous variables that might otherwise influence the dependent variable. In psychological experiments, extraneous variables can seldom be controlled directly, partly because people differ from one another in ways that affect their behaviour. You may think it’s impossible to control for all individual differences and other extraneous variables, but in fact there is a remarkable solution to this problem.

In 1926, the British statistician Ronald Fisher discovered a powerful method of control called randomization. By assigning subjects or participants to an experimental group and a control group strictly at random, and then treating the two groups identically apart from the manipulated independent variable (applied to the experimental group only), an experimenter can control, at a single stroke, for all individual differences and other extraneous variables, including ones that no one has even considered. Randomization does not guarantee that the two groups will be identical but rather that any differences between the groups will follow precisely the known laws of probability.

This explains the purpose and function of statistical significance tests in psychology. For any observed difference, a significance test enables a researcher to calculate the probability that a difference at least as large as the observed difference could occur by chance alone. The researcher then knows what the probability is of such a large difference under the null hypothesis – the working hypothesis that the independent variable has no effect. If the probability under the null hypothesis is sufficiently small (by convention, usually less than 5 per cent, often written p < .05), then it is reasonable to conclude that the observed difference is probably not due to chance, and if it is not due to chance, then it must be due to the independent variable, because all other variables that could explain it have been controlled by randomization.

If this immensely powerful idea were more widely understood, then people would be less vulnerable to illusory correlation, more sceptical about merely anecdotal evidence, and capable of interpreting findings from any survey research, case study, correlational study, observational study, or quasi-experiment with appropriate caution.

What do you think is the most commonly held misconception in your subject area?

Although I can’t prove that it’s the most common, the most fashionable misconception is the assumption that phenomena of behaviour and mental experience – the subject-matter of psychology – can be understood and explained exclusively in terms of neural mechanisms. It is sustained by the increasingly popular doctrine that neuroscience can in principle replace traditional psychology, that it is already replacing traditional psychology, or (in its strongest form) that it has already replaced traditional psychology. This is a debilitating form of reductionism, based on the assumption that behaviour and mental experiences are closely correlated with neural processes, especially in the brain; but locating a mechanism in the brain does not amount to explaining the associated psychological phenomenon, as I can easily show with a Gedankenexperiment (thought experiment) and an example from nature.

First, imagine a super-intelligent alien trying to understand a working computer busy printing out my Dictionary of Psychology on a laser printer. By merely investigating the physical mechanism of the computer and the printer, it would never understand what the computer was actually doing; or at least its explanation would lack what is most important and interesting about the computer’s behaviour.

Second, purposeful behaviour can occur naturally without any involvement of neural mechanisms. For example, the unicellular paramecium, found abundantly in stagnant ponds, moves about, avoids obstacles by swimming round them, gathers food, and retreats from danger. It can turn round in a glass tube to escape, and it can even learn from experience, although some neuroscientists unsurprisingly question whether this is true learning. Yet a paramecium has no nervous system, and its single cell is not even a neuron; therefore, it provides conclusive evidence that neuroscience cannot explain all forms of behaviour.

In your opinion, which is the most fascinating entry in your dictionary and why?

Being asked to choose the most fascinating entry is like being asked to choose one’s favourite child, and I won’t do it. I find thousands of the entries fascinating, but the entry defining heuristic, together with the various specific heuristics cross-referenced from it, describes ideas that have fascinated others sufficiently to be rewarded with the only two Nobel prizes ever awarded for purely psychological research. A heuristic is a rough-and-ready procedure or rule of thumb for making a decision, forming a judgement, or solving a problem, and we all use heuristics all the time. The US researcher Herbert Simon introduced the term in its modern psychological sense in 1957 to explain how human decision makers with bounded rationality solve problems when they do not have the time or resources to examine all available possibilities thoroughly, and he received the first Nobel Prize for this work. Two decades later, the Israeli-American psychologists Amos Tversky and Daniel Kahneman discovered and investigated experimentally a large number of biases in human thinking that can be traced to particular heuristics, and in 2002 Kahneman was rewarded for this work with the second Nobel Prize, Tversky having died a few years earlier.

A typical example is the conjunction fallacy: undergraduate students were shown personality sketches of a hypothetical person called Linda (young, single, deeply concerned about social issues, and involved in anti-nuclear activity) and asked whether it was more probable that Linda was a bank teller or that Linda was a bank teller who was active in the feminist movement. No fewer than 86% of the students judged it more probable that that Linda was a bank teller who was active in the feminist movement, although the probability of a conjunction A and B can never be greater than the probability of A. The fallacy arises from the use of the representativeness heuristic, according to which people estimate the probability that something belongs to a particular class by judging how typical it is of that class. Because Linda seems more typical of feminist bank tellers than of bank tellers in general, many people fall into the conjunction fallacy in this example.