This course introduces students to quantitative analysis and research methods. The course begins with a discussion of how quantitative methods fit within the broader research landscape. It then exposes students to basic descriptive statistics (including measures of central tendency and dispersion), the principles of statistical inference and important statistical tests and their practical application. By the end of the course, students will be comfortable with a variety of analytical tools relevant to urban planning and policy, including: hypothesis testing, t-tests, ANOVA, chi squared tests, correlation and multivariate regression.
The aim of the course is to introduce students to key concepts and tools in quantitative research methods and analysis. Most importantly, the goal is to develop students’ intuition regarding data analysis and the application of statistical techniques. By the end of the course students should be familiar with how basic techniques of quantitative analysis can be applied to a wide variety of data. Students should also have a sense of the strengths and weaknesses of quantitative data analysis and under what circumstances the tools learned in the class are best applied in practice. The course is a lecture course, but students will be expected to participate through classroom discussions, posing questions relevant to the course material and conversing with guest speakers. The course will be evaluated through in-class participation, three problem sets and a final project.