Dear Decision Sciences Collaborative,
| Welcome back! I hope that everyone had a rejuvenating and productive summer. I am honored to serve as the new Director of the DSC. My primary goal is to continue the excellence that Ian Krajbich established for this collaborative unit. I, for one, have benefited greatly from the opportunities that the DSC has provided to interact and collaborate with folks from other departments on campus. My hope is to foster these opportunities for all of you as well! If you have suggestions for any new programming, events, or activities for the collaborative, please let me know! As in past years, we will be holding our annual fall grant competition, with a deadline of October 16. Please see the DSC website for more information about applying: https://decisionsciences.osu.edu/funding-opportunities We look forward to seeing your new research ideas! I would like to remind everyone that the DSC owns an Eyelink eye-tracker, which is housed in the Department of Psychology, Lazenby Hall. This resource is available for use by members of the DSC. If you would like to use this resource, please contact Ariana Hernandez-Colmaneres. We also have a number of course announcements: BUSML 8250: Consumer Behavior Time: Mondays, 1 - 4 pm Instructor: Rebecca Reczek (E-mail to register) Course Description: This course is designed to serve as an overview of and introduction to academic research in consumer behavior. We will focus on research published in the elite marketing journals, the Journal of Consumer Research, Journal of Marketing Research, and Journal of Marketing. The course will be a seminar style course where we will discuss a set of academic articles on a specific theme each week. Psych 8890: Seminar in Decision Psychology Time: Friday 9 - 11:45 am Instructor: Roger Ratcliff (E-mail for more information) Course Description: This class is designed as an introduction to reaction time analysis and modeling. It is based on a forthcoming book that deals with these topics. The chapters in the book will serve as the basic readings for the course. There will be a number of class projects with R code that will provide the basic tools for looking at reaction times and then we will start to analyze real data. We will fit basic diffusion models to the data, and then use data from the students or go out and import data from published articles in the field of the student and find out what is wrong with the data and/or analyses. Currently, much work in psychology, neuroscience of decision-making, clinical and neuropsychology use models and methods that are flawed and the course will provide better methods and tools to examine data in detail. The design of the course will be flexible and aimed at the interests of the students. We can examine data from the student’s laboratory and field with the aim of having the student come from the course with a background in how to deal with reaction time data, how to fit simple models to data, and a knowledge of applications in areas of research and application relevant to the student's interests. ECON 8194: Experimental Economics Methodology Instructor: Paul J. Healy (E-mail for more information) Time: Tuesday and Thursday 9:35 - 10:55 am Course Description: This course will equip students with the tools needed to design, run, and analyze a laboratory experiment that conforms to the norms and expectations of the field of experimental economics. Broadly, the course will cover theoretical discussions of incentives in experiments, including elicitation techniques, as well as empirical research on those methods. Students will also learn relevant statistical techniques for experiments that are not taught in the standard econometrics course sequence. Next, students will receive an introduction to various programming interfaces used to design experiment software. Finally, students will learn and discuss ethical considerations when running experiments, including sample size calculations, p-hacking, and the appropriate use of pilot experiments. |
Best Regards,
Ken Fujita, DSC Director
fujita.5@osu.edu
