Experimental Design and Analysis II (Part II—Advanced) (2026 DSS)

About

Preference for strong causal evidence in publishing scholarly research at top journals has fueled interest in advanced experimental designs and analysis. Designing experiments and analyzing data for strong evidence of causal mechanisms is the focus of this course. Aimed at Ph.D. students and faculty who are motivated by interest in strong causal evidence using experimental designs in business (e.g., accounting, information systems, marketing, organizational behavior) and related disciplines (e.g., economics, psychology), this second course covers advanced concepts and tools for scholarly research. It is appropriate for scholars who have completed a foundational course (first-level) in experimental designs, and want to develop expertise. We will examine experimental designs and analyses from the perspective of an applied researcher, not from that of a statistician. Although there will be sufficient coverage of statistical concepts (to ensure that the procedures and techniques are applied intelligently), we will not focus on statistical theory per se. We will be using SPSS/Stata for course work with an option to use R/Python if the student is interested.

Course leader

Jagdip Singh, Case Western Reserve University, United States

Target group

The Doctoral Summer School online courses are aimed at doctoral students, post-docs, academics and professionals from different fields and from all over the world.

Fee info