Course details
Advanced Mathematical Tools in Management
MATH 40604A
This course aims to introduce or review the essential mathematical concepts, techniques, and tools necessary for understanding scientific literature and conducting research activities in various fields of quantitative management.
The topics are presented, starting from basic notions, in increasing order of complexity. The range of concepts covered does not allow for in-depth exploration of each; the objective is rather to foster understanding of the concepts and to introduce the contexts in which they are used.
The course includes an introduction to the fundamental mathematical concepts required for advanced studies in quantitative management: terminology, functions, matrix notation, random variables, systems of equations, and calculus. It then presents the foundations of optimization (models and methods) and statistical data analysis (estimation, forecasting, inference).
The course includes an introduction to the fundamental mathematical concepts required for advanced studies in quantitative management: terminology, functions, matrix notation, random variables, systems of equations, and calculus. It then presents the foundations of optimization (models and methods) and statistical data analysis (estimation, forecasting, inference).
Themes covered
Introduction and Foundations: Modeling and mathematical tools algebra sets proof techniques
Functions: Definition properties common functions time-dependent functions implicit functions
Matrix Notation and Algebra: Vectors matrices operations eigenvalues quadratic forms
Random Variables: Probability discrete and continuous variables density and distribution functions moments multivariate variables correlation
Systems of Equations: Solving linear and nonlinear equations analytical solutions numerical methods
Calculus: Derivatives differentiability Taylor series integrals numerical methods
Optimization: Modeling typology solution methods complementarity numerical techniques
Estimation: Research questions data sampling representativeness methods quality and asymptotic behavior
Forecasting: Inferential vs. predictive data analysis forecasting methods evaluation and validation
Statistical Inference: Model selection interpretability validation hypothesis testing
Important notes
Course in French : MATH 40604
Course code
MATH 40604A
Subject
Mathematics
Program
Graduate diplomas
Instruction mode
On-site learning
Credits
3