- Instructor of record: Jennifer Hurley
- Instructor of record: Gary McDonogh
- Instructor of record: Kai McGinn
- Instructor of record: Laura Surtees
- Instructor of record: Anqi Yan
This course is a hands-on introduction to the research process. It will provide students with the practical skills needed to design, conduct, and analyze original research of the complexity of a thesis-length project. Specifically, students will build knowledge and experience in:
RESEARCH DESIGN: Understanding the characteristics of a good research question, and how to craft one from your own interests and sense of a problem. Additionally, knowing what sort of research design is best suited to addressing your particular research question.
RESEARCH METHODS: Gaining competency with the methodological tools most frequently used by students interested in tackling urban research questions: quantitative methods involving analysis of pre-existing large-n survey data and the qualitative methods of case study, content analysis, and interviewing.
DATA ANALYSIS: Not equivalent to methods, but indispensable to a researcher’s methodology, is the question of data analysis. This course provides an understanding of basic descriptive and inferential statistical analyses, both in concept and in practice (we use Excel and SPSS for statistical analysis) and introduces more advanced statistical tests. No programming is required or taught. Additionally, students will gain experience in qualitative data analysis, including an introduction to computer-assisted qualitative data analysis (we use Nvivo and/or Dedoose for CAQDA).
RESEARCH DESIGN: Understanding the characteristics of a good research question, and how to craft one from your own interests and sense of a problem. Additionally, knowing what sort of research design is best suited to addressing your particular research question.
RESEARCH METHODS: Gaining competency with the methodological tools most frequently used by students interested in tackling urban research questions: quantitative methods involving analysis of pre-existing large-n survey data and the qualitative methods of case study, content analysis, and interviewing.
DATA ANALYSIS: Not equivalent to methods, but indispensable to a researcher’s methodology, is the question of data analysis. This course provides an understanding of basic descriptive and inferential statistical analyses, both in concept and in practice (we use Excel and SPSS for statistical analysis) and introduces more advanced statistical tests. No programming is required or taught. Additionally, students will gain experience in qualitative data analysis, including an introduction to computer-assisted qualitative data analysis (we use Nvivo and/or Dedoose for CAQDA).
- Instructor of record: Jennifer Hurley
- Instructor of record: Lauren Restrepo
- Instructor of record: Samuel Olshin
- Instructor of record: Daniela Voith
- Instructor of record: Jeffrey Cohen
- Instructor of record: Min Kyung Lee
- Instructor of record: Jamie Richardson Sandhu
- Instructor of record: Jeffrey Cohen
- Instructor of record: Min Kyung Lee
- Instructor of record: Min Kyung Lee
- Instructor of record: Gary McDonogh
- Instructor of record: Laura Surtees
- Other editing teacher: Margaret Kelly
- Instructor of record: Jeffrey Cohen
- Instructor of record: Jennifer Hurley
- Instructor of record: Meagan Kearney
- Instructor of record: Min Kyung Lee
- Instructor of record: Gary McDonogh
- Instructor of record: Kai McGinn
- Instructor of record: Samuel Olshin
- Instructor of record: Liv Raddatz
- Instructor of record: Lauren Restrepo
- Instructor of record: Matthew Ruben
- Instructor of record: Tiffany Stahl
- Instructor of record: Daniela Voith
- Instructor of record: Min Kyung Lee
- Instructor of record: Jeffrey Cohen