30449 - MATHEMATICS - MODULE 2 (APPLIED MATHEMATICS)
Department of Decision Sciences
Course taught in English
SIMONE CERREIA VIOGLIO
Suggested background knowledge
Mission & Content Summary
MISSION
CONTENT SUMMARY
- Implicit functions.
 - Constrained optima; classical programming and differentiable non linear programming.
 - Integral Calculus
 - Complex Numbers
 - Eigendecomposition of a square matrix. Power and exponential matrices,
 - Dynamical systems; ordinary differential equations, finite difference equations. Glossary and properties.
 - Solving separable and linear autonomous equations.
 - Stability; the linear autonomous case, linearization method in the non linear autonomous case. Autonomous systems of dimension 1; phase and stairstep diagrams.
 
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Recognize the mathematical model and its main properties.
 - Describe a mathematical model and list the assumptions that must hold in order that the model may be correctly applied.
 - Select and reproduce the correct procedures for solving a static optimization problem, for computing integrals, for assessing the asymptotic behavior of a dynamical system and for finding its trajectories.
 
APPLYING KNOWLEDGE AND UNDERSTANDING
- Apply the learned calculus methods to solve an optimization problem, to compute integrals, to analyze the asymptotic behavior of a dynamical system, to compute the solutions of a differential/difference equation.
 - Demonstrate the main properties of a model.
 - Formulate in a proper way the assumptions which are required to apply the mathematical tool.
 
Teaching methods
- Lectures
 - Practical Exercises
 
DETAILS
Teaching and learning activities for this course consist of (1) face-to-face-lectures and/or online lectures, (2) in class exercises.
- During the lectures convenient examples and applications allow students to identify the quantitative patterns and their main logical-mathematical properties.
 - The in class exercises allow students to properly apply the analytical tools in practice.
 
Assessment methods
| Continuous assessment | Partial exams | General exam | |
|---|---|---|---|
  | 
						x | x | 
ATTENDING AND NOT ATTENDING STUDENTS
The exam is written. Each student can choose whether to take:
General Exam: a single final exam (labelled with S). The General Exam is worth 100% of the final grade.
Partial Exam: 2 partial written exams (labelled with I). Each partial written exam is worth 50% of the final grade (100% in total).
Both the General and the Partial written exams consists of open answer questions which aim to assess the students’ ability to:
- Apply in a proper way the learned calculus methods in order to compute integrals, to solve optimization problems and differential/difference equations.
 - Describe the notions and the methods learned.
 - Justify in a proper manner the achieved conclusions.
 
- Recognise and demonstrate the connections between the main concepts and their properties.
 
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
- 
	
S. CERREIA-VIOGLIO, M. MARINACCI, E. VIGNA, Principles of Mathematics and Economics, draft version (March 2022). Available on BBoard in PDF format.
 - 
	
R. K. SUNDARAM, A First Course in Optimization Theory, Cambridge University Press, 1996, ISBN: 978052149770.
 - M. CIGOLA, L. PECCATI (2019), Dynamical Systems, PDF available on Bboard.
 - Past written exams with solutions, PDF available on Bboard.