Professor Feinstein's classes at SOM
The Practice and Management of Creativity & Innovation
(828b, taught in the Spring, half course) - Syllabus
This is an elective course for SOM students and other interested Yale students about the creative process and the management of this process. We describe and discuss basic features of the creative process, both short-term and over longer time periods, a number of different psychological approaches to creativity, and important issues involved in managing creativity effectively, including leadership, project management, incentives, and response to change. Basic issues include: fostering our own creativity and the creativity of those around us; paths of creative development of individuals engaging in creative endeavors; obstacles to creativity; brainstorming; and the nature of creativity in teams and organizations. We study creativity in many domains, including business, science and technology, the arts, and life in general, relying on a mixture of lectures, readings, creativity exercises, cases, and general discussion.
(403, Fall term - 8 Classes) — Syllabus (coming soon)
Core statistics for our MBA students. Main topics are hypothesis testing and confidence intervals, simple estimation, and an introduction to basic regression, including independent and dependent variables, key assumptions of the regression model, how to interpret regression output, and discussion of practical issues and applications including causality and variable selection. STATA is used in the course.
(829b, taught in the Winter, half course) — Syllabus
This is an elective course for SOM and other interested Yale students that provides training in statistical modeling. We study a host of models, based in regression and maximum likelihood techniques, and cover applications of the models using STATA. Models we cover include: ordinary least squares and why and how it works; qualitative response models, including probit, logit, multinomial logit, and ordered probit; censoring and the tobit model; time series, including ARMA, ARCH/GARCH models, and the basis of random walk models; panel data; instrumental variables; and maximum likelihood modeling. Students assemble their own dataset and build and estimate models using their dataset in STATA. They also make presentation in class, honing their presentation skills and learning how to interrogate others presenting statistical models and results.
Math Boot Camp
(taught in the Summer)
A minicourse for students who need/want an extra boost of math preparation heading into the SOM first year core curriculum.
In addition to these courses, Professor Feinstein designed and launched the Careers and Innovator’s Perspective core courses in the new integrative SOM curriculum.