Basic mathematics

The laboratory aims at providing basic tools for the quantitative analysis of economic phenomena.
The approach is of a practical nature and students will apply statistical concepts to real world
situations. The statistical software package R will be used extensively throughout the course. At the
end of the lab, students should be able to carry out a regression analysis, apply model selection
procedures and explain statistical results.

The first part of the lab will be devoted to a short introduction of the R programming language. Its
syntax and object oriented language will be presented, as well as some facilities for data
manipulation, calculation and graphical display.

The main part of the lab will then focus on data analysis through regression methods. These
methods deal with modelling how one characteristic (expenditures, prices, sales, etc.) varies with
one or several other characteristics (income, gender, cost of work, supply, etc.). The scope of
regression modelling that will be covered includes multiple regression analysis with categorical
effects, interactions, panel structure, model choice and regression diagnostic procedures.

• 1.  (A) Julian J. Faraway Linear Models with R Chapman & Hall/CRC, Boca Raton, 2014 » Pagine/Capitoli: 1-16

Data sets, supplementary readings, and teaching material supplied by the teacher.

• Practical classes in a computing lab. Weekly assignment of homework and readings. In-class
  discussion of homework and readings.

• A regression analysis of a dataset using the tools learnt throughout the course. The analysis should
  be done individually as a take-home project and results should be presented as a written report.
  The aim is to evaluate the ability of the student to apply regression in a practical context. The report
  should then be shortly discussed with the teacher in order to evaluate the comprehension of
  theoretical issues.

English

English