Geography: Quant Methods in Human Geog

See Schedule of Courses for specific titles.

Six hours in Geography or Heath and Society. PACE students with permission and override Special Topics courses cannot carry CC designations

From census and geospatial datasets to surveys of social factors and health, numbers offer powerful ways to understand how people and places are connected, but they never speak for themselves. Quantitative Methods in Human Geography introduces students to the data and statistical tools geographers use to describe, test, and explain spatial and social relationships. We will explore how quantitative evidence reveals patterns and inequalities in neighborhood exposures, urban density, and access to resources; how it helps test ideas about migration or neighborhood change; and how it can both illuminate and obscure relationships between humans and their environments. Through lectures, guided exercises, and applied examples, students will learn how to move from questions to data, from data to analysis, and from analysis to meaningful interpretation. The course emphasizes the logic of statistical reasoning—summarizing information, testing hypotheses, and exploring relationships—while connecting these methods to real-world geographic questions about populations, communities, and environments.

This course combines lecture and in-class guided exercises. Students should expect to spend 6-8 hours a week on coursework outside of class. Required textbook for this course is Ha, R. and J. Ha, Integrative Statistics for the Social & Behavioral Sciences. 2012, Thousand Oaks, CA: Sage Publications (ISBN-13 978-1412987448). Upon completion of this course, students will be able to: • Identify and describe different types of data and measures related to people, place, and space. • Read and interpret quantitative research in geography and related social sciences. • Apply foundational statistical techniques to summarize, analyze, and visualize social and spatial data. • Use spreadsheet and statistical software (Excel, R, and/or Stata) to organize and present results. • Explain the logic of quantitative reasoning (including probability, sampling, and inference) and its role in geographic inquiry. • Connect quantitative findings to broader questions about inequality, human–environment interactions, and place-based processes.

Students will be evaluated through applied in-class and take-home exercises, a midterm exam, and a comprehensive final exam. Exercises will combine calculation, interpretation, and written explanation, encouraging students to demonstrate both technical skill and conceptual understanding. Participation and engagement in class discussions and applied labs will contribute to the overall course grade.