1.7 Theories, hypotheses and predictions

Your study will definitely have (at least one) research question. It may or may not have any hypotheses. 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, other than 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. You could form the hypothesis that people living in your city were getting lonelier over time, and seek evidence to test that hypothesis, without there being any general theory from which this hypothesis arises.

Hypotheses are statements concerning how phenomena or constructs relate to one another (time and loneliness, for example). Often, though not always, they concern causal relations. A study might support a hypothesis, thus strengthening the evidence for the claim that the hypothesis is true, or fail to support it, weakening the evidence for the claim that the hypothesis is true. A hypothesis is a much narrower thing than a theory, and as mentioned above, it need not arise from a theory.

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 operationalise 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 people in my city are getting lonelier over time. I decide to operationalise this by choosing a random sample of residents. Each year for ten years, I will send them a message and ask them how many other people they have talked to that day. My hypothesis is that people are getting lonelier over time. My prediction is that the average number of people talked to will be lower in year 5 than in year 1. Thus, the hypothesis is about the thing in the world I want to know about (change in loneliness over time), and the prediction is about the specific variables that I have chosen to study it (difference in average number of people talked to that day).

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 to be 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.