DBA 8113 : Quantitative Research Methods I
3 credits
Only open to DBA students
This is the first course in the quantitative research methods series, designed to introduce students to the major quantitative approaches in management research. The first part of the course provides an overview of the major quantitative research methods in management research. Students will learn the foundations of experimental, quasi-experimental, and non-experimental methods. They will understand the strengths, limitations, and requirements of each method and will be able to select the most suitable method for their research projects based on their circumstances, budgetary, and time constraints. The larger component of the course reviews data and statistical concepts and tools that underpin the major quantitative methods mentioned above. These include quantifying managerial phenomena, mean testing, ANOVA, various aspects of linear regressions, hypothesis testing, and an introduction to Structural Equation Modeling (SEM). Furthermore, the course covers effective visualization techniques to communicate findings and craft compelling stories. Students will also learn to use Generative AI as their tutor and assistant. Additionally, students will develop the skills to read and interpret scholarly articles that apply the quantitative analyses taught in this course. Ultimately, the course aims to prepare students for their dissertation and group projects in the Lab for Business-Driven Research I and II courses.