Title: Theory, evidence and measurement
Course: UGQuants (SSPS) > Section: Introduction to Quantitative Analysis

Theory, evidence and measurement

Quantitative analysis is not something we do merely to generate and present numbers: we are fundamentally interested in what these numbers can tell us about our social and political environment.

Especially when we carry out quantitative analysis from an academic perspective, this usually involves some kind of engagement with theory. ‘Theory’ could mean anything from a ‘macro’ or ‘grand’ theory about the social world (e.g. Liberalism or Marxism) to a modest proposition (e.g. women do more housework and childcare than men because of the persistence of gendered attitudes to domestic labour). Research is the process of testing, modifying and/or creating such theories. In order to do this we need empirical evidence.

To put it simply, if we want to be analysts of the social and political world we need to take a systematic approach to collecting and reflecting on our observations of that world. ‘Observation’ might be taken quite literally, to mean e.g. the visual observation and recording of human behaviour (or some aspect of it) within its real life context. Or, more broadly, we can understand ‘observation’ to mean any piece of empirical evidence or ‘data’ that we produce. In quantitative analysis, this evidence is numerical.

This short video will raise your awareness when conducting a visual observation

However, this might create the misleading impression that quantitative analysts are only concerned with those features of the social and political world that have (or at least seem to have) some kind of inherent numerical quality. It is true that sometimes we are interested in such things (e.g. age; income; number of votes), but engaging with theory also entails dealing with social and political concepts that do not seem to have any inherent numerical quality, such as culture, social class, and political partisanship.

Essential to quantitative analysis is that we try to find a way to measure such concepts (or aspects of them) in such a way that they can be represented numerically. Hence it is the concepts that are being represented that we really want to investigate: the numbers are just a way to allow us to do that. The process by which we develop (non-numerical) concepts into something (numerically) measurable may be referred to as operationalization, although you should note that this term has a wider meaning that extends beyond quantitative approaches: it is a means of making researchable the issues and questions that concern us.