Spring 2020

CRP 381M.1

Planners today, more than ever, must operate in a world overflowing with data. Just as planners who primarily gravitate towards statistical models and GIS must nonetheless acquire basic competence with qualitative techniques such as interviews and community participation processes, those who are more qualitatively oriented cannot escape data and data analysis. Our core methods curriculum in the Community and Regional Planning Program is designed to make sure that everyone moving through the program has a solid foundation in both the yin and the yang of quantitative and qualitative methods. CRP 381M is intended to help students “learn to love the data.”
 
CRP 381M has five basic goals. First, upon completing the course students will have a basic facility with gathering data from a particular source: the United States Census Bureau. There are, of course, many sources of data, but census data is so fundamental to planning that it is emphasized most heavily here. Students will learn how to gather and interpret social-demographic data from the decennial census and the American Community Survey (ACS), and gain at least a passing familiarity with housing data from the American Housing Survey (AHS), and economic data via Longitudinal Employer-Household Dynamics (LEHD) and County Business Patterns (CBP). Certain students will inevitably be more interested in dealing with census data from other nations; however, learning how to gather and interpret information from the US Census will be useful background when applied to other contexts. 
 
Second, we will also briefly “get under the hood” in order to understand how population projections are produced. Since planning is a future-oriented discipline, planners must rely on widely-agreed upon demographic forecasts to make reasonable decisions about allocating resources in the future. Demographic forecasting could be the subject of a whole course unto itself, but in CRP 381M students will get at least an introduction to how official forecasts of this type are made.  
 
Third, students are able to critically unpack the equity implications of sociodemographic data metrics and classification schemes. Sociodemographic data—measuring or classifying people according to contested categories and quantities such as race, ethnicity, citizenship status, gender, employment status, income, poverty, and a host of others—is not inherently neutral or objective. It is instead a human creation, imbued (like all human creations) with all of the inevitable biases and blind spots of its creators, no matter who they are and no matter what particular choices they make. This by no means invalidates the usefulness or legitimacy of sociodemographic data; but it is vital for students to develop a basic understanding of the choices and tradeoffs that go into creating them, so that they may best understand exactly what they reveal and, importantly, what they conceal.  
 
The fourth goal is for students to learn how to communicate with data in both oral and written form. Knowing (and loving) the data is not enough for planners: informing other people, in particular laypeople, what a given set of data implies is a vital skill for planners. In CRP 381M, we will talk about how to present data, and what to avoid, so as to maximize quantitative methods’ power to educate and minimize their propensity to confuse.    
 
The final goal is for students to become savvy consumers of statistical analyses. CRP 381M is not a classic, in-depth statistics class: we will not, for example, be doing mathematical derivations of statistical formulas (although we will use some of the formulas—just as most of us don’t need to understand what’s under the hood in order to drive a car). But students will emerge from the class with a basic comfort with how to interpret the results of three key statistical techniques: hypothesis tests, surveys, and simple regressions. Students will also, along the way, learn how to do their own analyses using these three basic techniques, but the primary emphasis here is on how to interpret their results. A world awash in data is also a world awash in poorly-justified statistical claims: CRP 381M will help students learn how to sharpen their critical faculties and sort out the sound statistical assertions from the dubious ones.
 
CRP 381M is designed, as much as possible, to present material in an “inductive” manner, generalizing from specific examples, rather than in a “deductive” fashion (starting from abstract principles and then proceeding to specific examples) as is usually the case in traditional statistics courses. Without question, some students will go on to seek out more advanced statistical courses in CRP or elsewhere at UT. However, CRP 381M is intended to provide a basic foundation that even more qualitatively-oriented students can draw upon throughout their planning careers.