Quantitative “large N” research is currently the best way to make scientific inferences about large populations (people, animals, neighborhoods, etc.). Unlike qualitative “small N” research, which aims to intensely investigate the workings of a phenomenon in several cases, quantitative “large N” studies investigate phenomena among dozens, hundreds, and preferably thousands of cases, albeit less thoroughly per case than “small N” studies. Furthermore, quantitative studies rely on mathematical methods—like statistical analysis—rather than humanistic methods like interviewing (although quantitative studies might still use interviews). While “small N” studies are better able to articulate complex causal mechanisms, they are less able to make broad inferences about large populations—something one often wants to do in science. Although many people believe statistical analysis to be the most daunting and opaque part of quantitative research, in reality the greatest bulk of total study time is spent setting up the study, gathering data, and making sure data is analysis-ready. This course aims to teach the basics of how to structure and, to some extent, conduct a quantitative “large N” research study. It is designed for diverse audiences; graduate degrees are not necessary nor are degrees in particular fields. After completing the course, students should be able to lead simple research studies on their own and to assist in leading complex studies. The framework presented here can be applied to any question one wants to answer with data; it need not be an academic study intended for peer-reviewed journal publication. Studies can be conducted in businesses, schools, non-profit organizations, or anywhere else where one is dealing with mathematically measurable concepts. Perhaps even more important than being able to conduct a study, this course can help students learn how to think about everyday problems more scientifically.
What am I going to get from this course?
- Understand the basics of how to structure and, to some extent, conduct a quantitative "Large N" research study
- Lead simple research studies on their own, and assist in leading complex studies