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1 - 10 of 147 results for: MS&E

MS&E 20: Discrete Probability Concepts And Models

Concepts and tools for the analysis of problems under uncertainty, focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, belief networks, random variables, conditioning, and expectation.
Terms: not given this year | Units: 4 | UG Reqs: WAY-FR | Grading: Letter (ABCD/NP)

MS&E 52: Introduction to Decision Making

How to ensure focus, discipline, and passion when making important decisions. Comprehensive examples illustrate Decision Analysis fundamentals. Consulting case studies highlight practical solutions for real decisions. Student teams present insights from their analyses of decisions for current organizations. Topics: declaring when and how to make a decision, framing and structuring the decision basis, defining values and preferences, creating alternative strategies, assessing unbiased probabilistic judgments, developing appropriate risk/reward and portfolio models, evaluating doable strategies across the range of uncertain future scenarios, analyzing relevant sensitivities, determining the value of additional information, and addressing the qualitative aspects of communication and commitment to implementation. Not intended for MS&E majors.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Robinson, B. (PI)

MS&E 101: Undergraduate Directed Study

Subject of mutual interest to student and faculty member. Prerequisite: faculty sponsor.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit | Grading: Letter or Credit/No Credit

MS&E 107: Interactive Management Science (MS&E 207)

Analytical techniques such as linear and integer programming, Monte Carlo simulation, forecasting, decision analysis, and Markov chains in the environment of the spreadsheet. Probability management. Materials include spreadsheet add-ins for implementing these and other techniques. Emphasis is on building intuition through interactive modeling, and extending the applicability of this type of analysis through integration with existing business data structures.
Terms: Aut, Sum | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR | Grading: Letter or Credit/No Credit

MS&E 111: Introduction to Optimization (ENGR 62)

Formulation and analysis of linear optimization problems. Solution using Excel solver. Polyhedral geometry and duality theory. Applications to contingent claims analysis, production scheduling, pattern recognition, two-player zero-sum games, and network flows. Prerequisite: CME 100 or MATH 51.
Terms: Win, Spr | Units: 4 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit

MS&E 120: Probabilistic Analysis

Concepts and tools for the analysis of problems under uncertainty, focusing on focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, random variables, distributions, conditioning, expectation, change of variables, and limit theorems. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 5 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit
Instructors: Shachter, R. (PI)

MS&E 130: Information Networks and Services

Architecture of the Internet and performance engineering of computer systems and networks. Switching, routing and shortest path algorithms. Congestion management and queueing networks. Peer-to-peer networking. Wireless and mobile networking. Information service engineering and management. Search engines and recommendation systems. Reputation systems and social networking technologies. Security and trust. Information markets. Select special topics and case studies. Prerequisites: 111, 120, and CS 106A.
Terms: Win | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter (ABCD/NP)
Instructors: Bambos, N. (PI)

MS&E 152: Introduction to Decision Analysis (MS&E 152W)

How to make good decisions in a complex, dynamic, and uncertain world. People often make decisions that on close examination they regard as wrong. Decision analysis uses a structured conversation based on actional thought to obtain clarity of action in a wide variety of domains. Topics: distinctions, possibilities and probabilities, relevance, value of information and experimentation, relevance and decision diagrams, risk attitude. Students seeking to fulfill the Writing in the Major requirement should register for MS&E 152W.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit
Instructors: Shachter, R. (PI)

MS&E 152W: Introduction to Decision Analysis (MS&E 152)

How to make good decisions in a complex, dynamic, and uncertain world. People often make decisions that on close examination they regard as wrong. Decision analysis uses a structured conversation based on actional thought to obtain clarity of action in a wide variety of domains. Topics: distinctions, possibilities and probabilities, relevance, value of information and experimentation, relevance and decision diagrams, risk attitude. Students seeking to fulfill the Writing in the Major requirement should register for MS&E 152W.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit
Instructors: Shachter, R. (PI)

MS&E 174: Social Entrepreneurship Collaboratory (URBANST 133)

Interdisciplinary student teams create and develop U.S. and international social entrepreneurship initiatives. Proposed initiatives may be new entities, or innovative projects, partnerships, and/or strategies impacting existing organizations and social issues in the U.S. and internationally. Focus is on each team¿s research and on planning documents to further project development. Project development varies with the quarter and the skill set of each team, but should include: issue and needs identification; market research; design and development of an innovative and feasible solution; and drafting of planning documents. In advanced cases, solicitation of funding and implementation of a pilot project. Enrollment limited to 20. May be repeated for credit. Prerequisites: 131 and 132, or consent of instructor.
Terms: Aut, Win | Units: 4 | UG Reqs: WAY-SI | Repeatable for credit | Grading: Letter (ABCD/NP)
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