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121 - 130 of 155 results for: MS&E

MS&E 353: Decision Analysis III: Frontiers of Decision Analysis

The concept of decision composite; probabilistic insurance and other challenges to the normative approach; the relationship of decision analysis to classical inference and data analysis procedures; the likelihood and exchangeability principles; inference, decision, and experimentation using conjugate distributions; developing a risk attitude based on general properties; alternative decision aiding practices such as analytic hierarchy and fuzzy approaches. Student presentations on current research. Goal is to prepare doctoral students for research. Prerequisite: 352.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Howard, R. (PI)

MS&E 355: Influence Diagrams and Probabilistics Networks

Network representations for reasoning under uncertainty: influence diagrams, belief networks, and Markov networks. Structuring and assessment of decision problems under uncertainty. Learning from evidence. Conditional independence and requisite information. Node reductions. Belief propagation and revision. Simulation. Linear-quadratic-Gaussian decision models and Kalman filters. Dynamic processes. Bayesian meta-analysis. Prerequisites: 220, 252, or equivalents, or consent of instructor.
Terms: Win, alternate years, not given next year | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Shachter, R. (PI)

MS&E 365: Advanced Topics in Market Design

Primarily for doctoral students. Focus on quantitative models dealing with sustainability and related to operations management. Prerequisite: consent of instructor. May be repeated for credit.
Terms: Spr | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: Ashlagi, I. (PI)

MS&E 371: Innovation and Strategic Change

Doctoral research seminar, limited to Ph.D. students. Current research on innovation strategy. Topics: scientific discovery, innovation search, organizational learning, evolutionary approaches, and incremental and radical change. Topics change yearly. Recommended: course in statistics or research methods.
Terms: Win | Units: 2-3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: Katila, R. (PI)

MS&E 372: Entrepreneurship Doctoral Research Seminar

Classic and current research on entrepreneurship. Limited enrollment, restricted to PhD students. Prerequisites: SOC 363 or equivalent, and permission of instructor.
Terms: Win | Units: 1-3 | Grading: Letter or Credit/No Credit
Instructors: Eesley, C. (PI)

MS&E 374: Cross Border Regional Innovation

This is an advanced research seminar class that is restricted to students that had taken MS&E 274. Disruptive innovation is the realization of new value proposition through establishment of a new ecosystem. Value proposition depends on the culture and social value in a particular region; while the ability to establish the ecosystem to realize the value proposition is highly dependent on the firm¿s knowledge and skills to operate effectively under the political, social, and economic structure of that particular region. Therefore cross border and regional innovations in different regions will take different path. This course will examine cases that cover innovations in developing economy, cross border e-commerce, and international business groups.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 376: Strategy Doctoral Research Seminar

Classic and current research on business and corporate strategy. Limited enrollment, restricted to PhD students. Prerequisites: SOC 363 or equivalent, and permission of instructor. Course may be repeated for credit.
Terms: alternate years, given next year | Units: 3 | Repeatable for credit | Grading: Letter (ABCD/NP)

MS&E 379: Social Data Analysis

Applied introduction to good empirical research and causal inference for social scientists and others analyzing social data. Designed to provide an introduction to some of the most commonly used quantitative techniques for causal inference in social data including: survey design and inference, regression and propensity score matching, instrumental variables, differences-in-differences, regression discontinuity designs, standard errors, and the analysis of big data. Applications: organizations, entrepreneurship, public policy, innovation, economics, online education, visual representations, communication, critique and design of figures, graphs. Does not explicitly cover social network structure or machine learning as these topics are well-covered elsewhere. Students work in groups and individually to design and carry out a small research project based on the use of analytics, large data sets, or other digital innovations related to business or other organizations. Students become acquainted with a variety of approaches to research design, and are helped to develop their own research projects. Course prioritizes a thorough substantively grounded understanding of assumptions over mathematical proofs and derivations. Aimed at PhD students, but open by permission to Master's students and to students in other Stanford programs with relevant coursework or experience in analytics and statistics.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 380: Doctoral Research Seminar in Organizations

Limited to Ph.D. students. Topics from current published literature and working papers. Content varies. Prerequisite: consent of instructor.
Terms: not given this year | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

MS&E 381: Doctoral Research Seminar in Work, Technology, and Organization

Enrollment limited to Ph.D. students. Topics from current published literature and working papers. Content varies. Prerequisite: consent of instructor.
Terms: not given this year | Units: 2-3 | Repeatable for credit | Grading: Letter or Credit/No Credit
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