OVERVIEW

Although what political scientists care about is discovering whether causal relationships exist between concepts, what we actually examine is statistical associations between variables. Therefore it is critical that we have a clear understanding of the concepts that we care about so we can measure them in a valid and reliable way. In this chapter we focus on two critical tasks in the process of evaluating causal theories: measurement and descriptive statistics. As we discuss the importance of measurement, we use several examples from the political science literature, such as the concept of political tolerance. We know that political tolerance and intolerance is a “real” thing – that it exists to varying degrees in the hearts and minds of people. But how do we go about measuring it? What are the implications of poor measurement? Descriptive statistics and descriptive graphs, which represent the second focus of this chapter, are what they sound like – they are tools that describe variables. These tools are valuable because they can summarize a tremendous amount of information in a succinct fashion. In this chapter we discuss some of the most commonly used descriptive statistics and graphs, how we should interpret them, how we should use them, and their limitations.