69213 - Mathematics for Social Sciences

Learning outcomes

Learning Outcomes: At the end of the course the student learns the basic and multivariate calculus ropes. These mathematical tools allow the student to set up and solve models arising in social sciences, as tourism, that are connected to unconstrained optimization for functions of one and several variables and to linear constrained optimization. Some up to date applications inherent in tourism sector are analysed in the laboratory.

Course contents

The fundamental contents of the course include mathematical notions that are unavoidable when studying models for social sciences as Tourism Economics.

They can be described as follows:

- Review of some topics in one-variable Calculus.

- Non constrained optimization for function of several variables.

- Some aspects of constrained optimization.

- Examples of mathematical models for tourism.

Readings/Bibliography

Some lectures notes will be distributed during the course, however all the topics can be found in the books:

K. Sydsaeter, P. Hammond, A. Strom "Essential Mathematics for Economic Analysis", Pearson

K. Sydsaeter, P. Hammond, A. Seierstad, A. S. "Further Mathematics for Economic Analysis", Prentice Hall

 

Teaching methods

Due to the different levels of mathematical skills, a crash course is organized before the lectures beginning. The attendance is strongly recommended.

During lectures students will be involved in some examples through a clicker system, a cellular phone can be useful.

Assessment methods

The written final test is based on the solution of ten exercises (3 points for each correct exercise). The oral part is optional.

The mark is out of 30 points, and the minimum required to pass the exam is 18/30. The first exam is scheduled before Christmas Holidays.

It is an opne book exam.

Registration for the exam is compulsory, and students have to register through AlmaEsami according to the general rules of the School of Economics and Management.

Student involvement through exercises solutions during lectures and personal work about papers is generally encouraged by the teacher.

 

Teaching tools

Each lecture is organized with an initial part based on the solution of exercises assigned in the previous lecture, an explanation of the new argument and finally some examplesabout its application.

Office hours

See the website of Maria Letizia Guerra