Crash courses

The Department of Economics, Management and Quantitative Methods (DEMM), offers the following crash courses to catch up with the basic mathematics, statistics and economics principles. Courses are open to all admitted students of the international master courses and offered by DEMM.

However, the attendance is recommended to all students (n.b: crash courses are only for admitted students).

Please notice that the crash courses do not give any credits therefore they cannot replace the other entry requirements.

How to register to crash courses

In order to register, you will have to fill in an online form.

Timetable and rooms 2019/20

The crash courses will start on August 26th, 2019 and will last for 3 weeks.

Rooms

  • Week 2 
    • Mon 2nd, room 302, via Festa del Perdono 3
    • Form Tue 3rd to Fri 6th, room M205 via Santa Sofia 9
  • Week 3:
    • Room 20, via Conservatorio 7.
Crash courses programs

Teacher:  Andrea Perchiazzo

40 hrs.

Starting date: August 2019

Course description and syllabus

  1. Introductory topics: algebra, equations, miscellaneous.
  2. Functions of one variables and their properties.
  3. Continuity and differentiability
  4. Single-variable optimization
  5. Integration
  6. Matrix and vector algebra. Determinants and inverse matrices.

References

  • Knut Sydsaeter, Peter Hammond, Arne Strom, Essential Mathematics for Economic Analysis, Pearson, ISBN-10: 0273760688 • ISBN-13: 9780273760689, 2012 (Chapters 1-9, 15-16).

Teacher: Elena Siletti

(non attending students can write her an email to get some didactic material of the crash course)

30 hrs.

Starting date: August 2019

 Course description and syllabus

  1. Review of probability and statistical inference
    1. Basic probability theorems: Central limit theorem, Law of large numbers etc.
    2. Some important discrete and continuous random variables – pdfs and cdfs.
    3. The Bayes rule and elements of Bayesian statistics.
    4. The likelihood function and the MLEs.
    5. Statistical estimation and testing
  2. Review of linear regression
    1. Simple linear regression.
    2. Multiple linear regression: parameters and OLS estimators.
    3. Multiple linear regression: SE of estimators, CI and testing.
    4. Multiple linear regression:  SER, R2, adjusted R2 and F.
    5. Further topics on linear regression analysis.

References

  • J Stock and M. Watson: “Introduction to Econometrics”, Pearson, 2011.
  • CB Moss: “Mathematical Statistics for Applied Econometrics”, Chapman and Hall/CRC,  2014.

Teacher: Ekaterina Shakina

40 hrs.

Starting date: September 2019

Course description and syllabus

This course focuses on the following topics: basic theory of consumer behaviour; production and costs; decisions under uncertainty;  partial equilibrium analysis: perfect competition, monopoly and oligopoly.

The exam consists of a written paper, with theoretical questions as well as exercises.

  1. Introduction. Market structure.
  2. Consumer theory. Budget constraint, preferences, utility function, optimal choice, demand function, price effects, consumer surplus, uncertainty.
  3. Market analysis. Aggregate demand, market equilibrium.
  4. Production theory. Technology, profit maximization and cost minimization, cost functions and firm supply.
  5. Market structure. Aggregate supply and perfect competition, monopoly, price discrimination, oligopoly.

References

  • Hal Varian, “Intermediate Microeconomics – a modern approach”, W. W. Norton & Company, 2009

Teacher: Massimo Walter Rivolta 

PDF files of the Computer Science lessons will be gradually available

Teacher: Isabella Pozzo