When you think of statistics, do you think of a helpful tool for real-world analysis, or does the phrase, “Lies, damn lies, and statistics” come to mind? Regardless of your answer to that question, Jeremy Weber wrote his new book, Statistics for Public Policy, for YOU. In this episode, host Russ Roberts welcomes Weber to talk about it.

Weber argues that no statistics textbooks include integration of context and purpose and audience with statistical analysis. That’s a problem. Roberts congratulates Weber for his use of illustrations rather than equations, and describes how he thinks of statistics in university as being more like a cooking class. Weber thinks of them more like vocational education; both are excellent analogies! Which one works best for you?

Of course, I have lots more questions I could ask… As always, we’ll limit it to a few, and we hope you’ll take a moment to share your thoughts. As Russ says, we love to hear from you!


1- How is learning statistics in school like a cooking class or learning how to use a chainsaw? What’s wrong with these ways of thinking about statistics? What does Weber mean when he compares concepts that are concept-dependent versus contextless? (Think of statistics versus physics, perhaps.)


2- Is statistical analysis more often used as a weapon or for truth-seeking in the political process? How do you think politicians would perceive Weber’s book, and why?


3- Roberts asks to what extent you can look at data without considering theory. How does Weber describe the proper relationship between data and theory? How does the increased computing power and quantity of data today make analysis harder? How might analysis today be more shallow at the same time as it has more data behind it?


4- The (in)famous distinction between correlation and causation is raised toward the end of the conversation. Roberts says one of the things he loved about Weber’s book is that he makes a point much deeper than that. What is that point? How ought we to consider the magnitude of causation, and how do analysts use statistical significance as a crutch?


5- Thus far the focus has been on what’s wrong with statistics and the way it’s taught. What did you take from this conversation about how it should be improved? Is a good understanding of statistics a requisite part of civic education? Why or why not?