DBA 8115: Quantitative Research Methods II
3 credits
Only open to DBA students
This is the second course in the quantitative research methods series. The first course provided an overview of experimental, quasi-experimental, and non-experimental methods along with foundational statistical tools underpinning them. This course provides a detailed review of these methods. By the end of the course, students can competently design and execute these methods. They will be able to analyze data, generate meaningful results, and communicate their findings effectively in both academic and non-academic outlets. Throughout the course, students expand their knowledge of statistical analysis and learn to use a statistical software package to implement these methods on data. Furthermore, students may learn advanced tools, such as structural equation modeling and machine learning techniques, to extract deeper insights from data. The integration of Generative AI throughout the course further enhances their ability to streamline analyses and research processes. They can also evaluate and critique quantitative methods in scholarly articles. This course will equip students with the quantitative skills needed for their dissertations and research projects after graduation.