1. Classes: Each class will be organized into lectures on the core subject and discussions of relevant urban planning examples as well as hands-on lab exercises of statistical packages. The lecture is scheduled on Wednesday, 10am-1pm in SDE SR14, but we will occasionally move to SDE CR4 for the lab sessions. There will be also several guest speakers sharing the real-world experience of using quantitative methods in urban planning research.
2. Module Requirements: The grade will be based on four components: problem sets, a final exam, an analysis project, and class participation.
1) Problem Sets: Four problem sets will account for 20% of the course grade. Unless otherwise stated, all problem sets are DUE one week after distribution. It will usually be possible to receive credit for problem sets that are up to one week late. After that date, no credit will be given for late problem sets. You are encouraged to work on problem sets in groups, but each individual is required to complete his/her own problem set. Copying the answers from someone else’s problem set is plagiarism and will be treated as such.
2) Final Exam: There will be a final exam at the end of the semester.
3) Planning Analysis Report Using Quantitative Methods: Students, working in small groups (max. 3 students), will use quantitative method(s) to address a real planning problem. Select a problem/decision of interest to you, and formulate the problem and construct hypotheses to be tested, collect the data, perform the statistical analysis, and write up your results. You may use data that have been collected and/or analyzed by other researchers, but you must clearly differentiate your analysis from their work. You are allowed to choose one or more statistical techniques that you have learned from the module (descriptive stats, comparison of means, correlation, linear regression, and etc.).
4) Class participation.
3. Computer Requirements: You will need access to a statistical software package (e.g., STATA, SAS, SPSS) for use in this module. Although you may use any package with which you are familiar for class assignments, the statistical labs during the lecture will be based on STATA.