30449 - MATHEMATICS - MODULE 2 (APPLIED MATHEMATICS)
Department of Decision Sciences
MARGHERITA CIGOLA
Suggested background knowledge
Mission & Content Summary
MISSION
CONTENT SUMMARY
- Differential calculus for functions of n real variables: partial derivatives, first order and second order differential.
- Implicit functions.
- Unconstrained optima. Constrained optima: classical programming and differentiable non linear programming.
- 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. One dimensional autonomous systems: phase diagram, stair step and cobweb diagrams.
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Recognize the mathematical model and its main properties.
- Identify a model and the assumptions that must hold in order that the model may be correctly applied.
- Reproduce the correct procedures for solving a static optimization problem, for assessing the asymptotic behavior of a dynamical system or for finding its trajectories.
APPLYING KNOWLEDGE AND UNDERSTANDING
- Apply the learned calculus methods to solve an optimization problem, 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
- Face-to-face lectures
- Online lectures
- Exercises (exercises, database, software etc.)
DETAILS
Teaching and learning activities for this course are divided into (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 | 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 I). The General Exam consists of open answer questions and is worth 100% of the final grade;
Partial Exam: 2 partial written exams (labelled with I) plus 2 online tests. Each partial written exam is worth 34% of the final grade (68% in total). Each online test consists of closed answer questions and is worth the 16% of the final grade (32% in total).
Both the General and the Partial written exams consists of open answer questions aimed to assess students’ ability to:
- Apply the analytical tools in order to solve optimization problems and differential/difference equations.
- Describe the notions and the methods learned.
- Justify in a proper manner the achieved conclusions.
The online tests consist of closed answer questions and aim to assess the students' ability to:
- Choose the correct mathematical tools to solve optimization problems and differential/difference equation;
- Apply in a proper way the learned calculus methods.
- Recognise the connection between the main concepts and their properties.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
- E. CASTAGNOLI, M. MARINACCI, E. VIGNA, Principles of Mathematics and Economics, Milano, dispense Egea, 2013, (ISBN 978-88-6407-192-3).
- E. CASTAGNOLI, M. CIGOLA (2019), Static Optimization, PDF available on Bboard.
- M. CIGOLA, L. PECCATI (2019), Dynamical Systems, PDF available on Bboard.
- Past written exams with solutions, PDF available on Bboard.