Methods of Planning Analysis
The course is designed to familiarize the student with the collection and numerical analysis of data for planning purposes. The intent of the course is to provide students an opportunity to conceptualize, define, design and implement planning-relevant research and analysis; covering both theory and application with emphasis on the latter. The planning methods covered are generally applicable to planning problems in more than one field and are considered basic tools. This course is not intended to serve as a graduate course in research methodology; rather our focus in this class is on the application of common tools of planning analyses and the presentation of planning analysis results.
The course consists of three sections that include (1) research design and basic statistical methods, (2) applied multiple regression, and (3) basic demographic and regional economic analysis techniques. Several individual problem sets will assist learning through practical applications of the material being presented. These problems sets are intended to reinforce classroom discussion and will not be graded.
Required Textbook: Applied Statistics for Public and Nonprofit Administration (8th Edition), 2012, by Meier, Brudney, and Bohte. Wadsworth Cengage Learning (available at UBS; also, click here to order from publisher ... note various alternatives including ebook)
Section I: Research Design and Basic Statistical Methods
September 4. Presentation of quantitative information, towards standardizing tabular and graphical presentation
September 10. Planning analysis semantics and terms
September 11. Basic research design appropriate for planning analysis
September 17. Data types, scales, and basic descriptive statistics
September 18. Concept of sampling, introduction to hypothesis testing
September 24. Example of sampling strategy, hypothesis testing - single mean and proportion
September 25. Hypothesis testing - single mean, proportion
October 1. Hypothesis testing - two means unpaired, two means paired, categorical data
October 2. Hypothesis testing - categorical data
October 8. Introduction to regression analysis
October 9. Regression analysis continued
October 15. Regression analysis continued and midterm review
October 16. Midterm I
Section II: Applied Multiple Regression
October 22. Midterm recap, introduction to multiple regression
October 23. Multiple regression models; terminology, multicollinearity, and model specification
October 29. Multiple regression models; multicollinearity, statistical tests, and interpretation (and, of course, model specification)
October 30. Multiple regression models; continue with examples using cross-sectional (CS) data
November 5. Multiple regression models; examples using CS data; data transformations
November 6. Multiple regression models; finish example using CS data; time series data and detecting autoregressive error structures
November 12. Finish content, recap, and review for midterm 2
November 13. Midterm 2
November 19. Guest Lecture - Mr. Hyun Kim on multiple regression time series analysis
Section III: Basic Demographic and Regional Economic Analysis Methods
November 20. Basic demographic analysis and component approaches to population projection.
November 26. Macro projections and population forecasting (download the article to be discussed in class here). Also, another article to read will be sent by email: Renski, H. and S. Strate. 2013. Evaluating alternative migration estimation techniques for population estimates and projections. Journal of Planning Education and Research 33(3): 325-335. Also, click here for a factsheet from the APL on migration by age cohort ... here is the website for the age-specific migration portal.
November 27. Directed study (read and understand Chapter 14 in SDM).
December 3. Descriptive tools of regional economics: Bifurcation methods (location quotients)
December 16. Midterm 3 (old exam here)