An Introduction to Data Analysis & Presentation
Prof. Timothy Shortell, Department of Sociology, Brooklyn College

Introduction

We are going to learn about quantitative data analysis. Before we begin looking at some of the basic tools, let's consider why sociologists quantify information in the first place.

Quantification has some advantages and disadvantages. It is ideally suited for some kinds of research topics and badly suited for others. The popular perception of science is that it must be quantitative; this is because it is widely believed that quantitative information is more objective, and therefore, a more accurate reflection of the true state of affairs. We shall see that this is a mistaken belief, and that both quantitative and qualitative information can be scientific.

The main reason that sociologists quantify information is to be able to construct and test mathematical models of the social world. We use quantitative variables as building blocks that fit together into a model of some social phenomenon. We build the model according to some body of sociological theory. We can then test some of the features of the model by collecting empirical data, and determining if the data turn out like the model predicts.

Mathematical models offer an elegant economy of expression. We can concisely state a model of some phenomenon with a small number of variables and their relations. For example, we might build a model to explain attendance at religious services. We might argue that religiosity causes attendance, and express the model as:

 X → Y

where X is the score on a religiosity scale and Y is frequency of attendance.

On the other hand, quantification has a couple of disadvantages. The social world is very complex, and much of our experience and behavior can't be easily quantified. As a result, quantitative information tends to simplify; the richness of detail is lost.

Mathematical models tend to give the impression that social processes are static, that is, that they work one way, have always worked one way, and will always work one way. They tend to minimize the extent to which the social world is constantly changing.

Some topics lend themselves to quantitative analysis. When we want to describe social forces and structures — what we call macro-sociology — we need to study large groups, like social classes, countries or social institutions. We want to be able to understand the general, or typical, case. It is very difficult to study very large groups without quantification.

Sometimes we want to study the details of a particular social process; we are more interested in narrative detail and lived context than in a summary of the typical case. Quantitative information is not always very useful in this kind of research. Qualitative methods are usually employed.

Sociologists don't have to employ only one method or the other. Frequently, both strategies are used to study a social problem or process, though one is usually emphasized. Most sociologists are pragmatists in practice. They use whatever tools are available to better understand their topic or question.

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