MGMT 350 - Decision Science

Units: 3 ; Breadth Area: GE-UDB
Problem solving and quantitative reasoning skills for effective decision making. Topics include decision analysis, optimization, simulation and forecasting. Emphasis is on formulating quantitative models to address real world problems and solving them using spreadsheet software.

Strongly Recommended Preparation: Upper division status (greater than 60 earned semester units) and completion of lower division Areas B1-B3.
Prerequisites: Completion of GE Areas A1, A2, A3 and B4 with grade C- (CR) or better; and either MATH 110 or MATH 130 or MATH 180 and STAT 110.
Possible Instructional Methods: On-ground or Online-Asynchronous.
Grading: A-F grading only.
Breadth Area(s) Satisfied: GE-UDB - Upper Division Science Inquiry and Quantitative Reasoning
Course Typically Offered: Fall & Spring

Student Learning Outcomes - Upon successful completion of this course students will be able to:

Demonstrate the knowledge of principles and techniques of quantitative methods in problem solving and scientific inquiry.
Apply the quantitative methods using software to solve problems, interpret results and write recommendations.
Demonstrate understanding of the frameworks and steps involved in problem solving and scientific inquiry, and the role of quantitative models in them.
Identify the role of quantitative techniques in data-driven decision making technologies.

UD-B. Upper-division Science Inquiry and Quantitative Reasoning Learning Outcomes

demonstrate advanced and/or focused science or quantitative content knowledge in a specific scientific field, using appropriate vocabulary and referencing appropriate concepts (such as models, uncertainties, hypotheses, theories, and technologies);
apply advanced quantitative skills (such as statistics, algebraic solutions, interpretation of graphical data) to scientific problems and evaluate scientific claims;
demonstrate understanding of the nature of science and scientific inquiry and the experimental and empirical methodologies used in science to investigate a scientific question or issue; and
apply science content knowledge to contemporary scientific issues (e.g., global warming) and technologies (e.g., cloning), where appropriate.