1.7 Theories, hypotheses and predictions

Your study will definitely have (at least one) research question. It may or may not have any hypotheses, but if it does have any, it will also have corresponding predictions. It may or may not be based on a theory. This section explains these different terms and how to apply them.

A theory is a comprehensive framework for predicting and explaining phenomena in a particular domain. A theory is a much more general kind of thing than any particular hypothesis or prediction (I will define those below). The relationship of theories to hypotheses is one-to-many: one theory can generate multiple different hypotheses that apply to specific situations. Theories can rarely be falsified (that is, shown to be wrong) by any single experiment. They stay around if they prove themselves consistently useful (or more useful than the available alternatives) across a range of empirical situations. Theories are not fixed targets: they are constantly being revised or modified to account for new phenomena or results. Theories tend to have a hard core of assumptions and claims, and then various modifiable additional bits that make them more usable empirically. Theories in psychology and behavioural science are varied in their precision and scope; if you want to understand an example of one, you could read up on Prospect Theory, for example.

Much research in psychology and behavioural science has no theory, if you exclude very general theoretical commitments, like the commitment to the scientific method and to revising beliefs in the light of evidence. This is not a criticism. If you studied some species of newly-discovered bird in Brazil, you could form the hypothesis that it had come in from Africa, and seek evidence for that hypothesis, without there being any general theory under test.

Hypotheses are statements how phenomena or constructs relate to one another. Often, they concern causal relations. A study might support a hypothesis, thus increasing the evidence for the claim that the hypothesis is true, or fail to support it, weakening the evidence that the hypothesis is true. A hypothesis is a much narrower thing than a theory, and as mentioned above need not arise from a theory. I could consider the hypothesis that restaurants in France are getting worse over time, without having any theory that predicts this or says why it should be the case.

Predictions are statements about the relationships between variables that we should expect if a hypothesis is true. What is the difference between a hypothesis and a prediction then? A hypothesis is couched in terms of the phenomena or constructs that we are studying, whereas a prediction is couched in terms of the variables we have used to operationalize those phenomena or constructs in our particular study. (Note that this way of using the two terms is not universally observed; it is just the way I find clearest).

For example, say my hypothesis is that restaurants in France are getting worse. I decide to operationalise this by choosing a random sample of 100 judges each year and sending each of them to a randomly selected restaurant. At the end of the meal they will rate their satisfaction with the meal on a scale of 1 to 10. I will do this now and in 20 years. My hypothesis is that restaurants in France are getting worse over time. My prediction is that the average satisfaction rating will be lower at the second time point than at the first. (This is not a very good study design by the way, I am just making the point). Thus, the hypothesis is about the thing in the world I want to know about, my estimand (restaurant quality in France), and the prediction is about the specific variables that I have chosen to study it, my estimator (average satisfaction on a scale of 1 to 10).

Predictions make a statement about how some aspect of the distribution of one variable (the outcome or DV) will vary according to the value of some other variable(s) (the predictors or IVs). Most often the prediction is about the average of the outcome or DV, but this is not necessarily the case. The prediction could concern the variation in the outcome, or the odds of the outcome happening if the outcome is an event rather than a continuous variable.

1.7.1 Exploratory and confirmatory research

Not all science tests hypotheses and predictions. Sometimes, you just want to understand how things relate to or affect one another, but you have a pretty open mind about what might be true. Research where you can’t state a small number of hypotheses and predictions ahead of time is called exploratory research. Where you do have specific hypotheses or predictions ahead of time, the research is called confirmatory, because you are using the study to confirm whether the hypothesis is supported, or not.

Confirmatory research is not better than exploratory research. Both are important aspects of the knowledge-making process. Patterns that are discovered in exploratory research can lead to the formation of hypotheses and tested in subsequent confirmatory research. This way we can establish if they were just one-offs or represent some more general regularity. The important thing is that researchers must always be clear upfront whether their research (or some part of it) is exploratory or confirmatory. Exploratory and confirmatory goals may well lead to you to analyse your data in different ways.