Quantitative Approach to Business Decisions - auce

Quantitative Approach to Business Decisions

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Course Code:

BBUS400

Course Hours:

45

Contact Hours / Week:

3

Prerequisite:

BSTA360, BMAT210

Co-requisite:

None

Course Description:

 

Business managers and directors used to rely on their experience and instinct to make tough decisions. In the era of big data, quantitative methods used by operations analysts and economists provide solid evidence to guide management decisions on production, distribution, marketing and personnel management. These methods also help managers’ project future business conditions, enabling them to adjust their strategies as needed. This course aims to provide students with an understanding of the quantitative methods for finance and investment. The course explains the mathematical and statistical applications relevant to modern financial instruments and risk management techniques.

Students will be able, at the end of this course, to apply basic statistical methods to analyze financial data and to develop financial models for financial decision making.

 

Course Learning Outcomes:

 

Upon successful completion of this course, students will be able:

  • Explain the fundamental concepts, basic assumptions, and major characteristics of various quantitative techniques of operations research;
  • Formulate and model real-life operations research problems mathematically, and solve them;
  • Interpret the theoretical workings of the simple method for linear programming, and perform iterations;
  • Perform sensitivity analysis to determine the direction and magnitude of change of a model's optimal solution as the data change, and make effective interpretations and decisions on the changed scenarios;
  • Solve specialized linear programming problem, such as, transportation problem;
  • Formulate real-life applications in terms of appropriate stochastic models;
  • Simulate a real system by experimenting with a model to use quantitative approach to decision making – both deterministic, as well as, probabilistic.

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