Insegnamento a.a. 2017-2018



Department of Decision Sciences

Course taught in English

Go to class group/s: 14
GIO (6 credits - I sem. - OB  |  SECS-S/01)
Course Director:

Classes: 14 (I sem.)

Course Objectives

This course aims to provide a high level of understanding of quantitative methods so that, after its attendance, students are able to perform data analysis to support management decision-making.
The course is delivered with an emphasis on introductory and advanced concepts of statistics for data analysis, where statistical techniques are taught in order to give students confidence in preparing accurate and informative data summaries, experiments, surveys and interpretation of research management reports. The practical activities are implemented using the specific statistical software STATA. It is essential that students develop skills for data processing as well as the interpretation of results.

Intended Learning Outcomes
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Course Content Summary

  • Simple and multiple regression.
  • Anova.
  • Longitudinal data analysis.
  • Factorial analysis.
  • Categorical data analysis.
  • Logistic regression.
  • Loglinear regression.

Teaching methods
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Assessment methods
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Detailed Description of Assessment Methods

  • Examination: 21/30.
  • Assignment: 9/30. 
At the end of the course there is an exam to test the knowledge acquired.
There is a written exam with questions and exercises on the topics taught in class (see the short description). The maximum grade for the final exam is 21 points.
Alternatively, students can complete two partial exams during the course. The maximum grade for the partial exams are 10 and 11 points respectively. If the second partial exam is not handed in, the student must take the final exam.
During the course there is also an assignment (empirical analysis) that students should perform on their own or in groups and hand in before the end of the course. This assignment is worth a maximum of 9 points. The grade of the assignment is valid also for the following academic years, hence do not need to repeat the assignment.
The examination procedures are the same for students who attend and do not attend the classes.


  • Slides and other materials from the course.
  • A. Agresti, B. Finlay, Statistical Methods for the Social Sciences, Prentice Hall, 2009, fourth edition.
Exam textbooks & Online Articles (check availability at the Library)


This course requires background knowledge of basic statistics such as introductory concepts of descriptive and inferential statistics. It is required to have attended at least one basic statistics course during a three-year degree. Students that have a superficial knowledge of statistics are highly invited that they attend the training course of statistics available before the start of the academic year.

Last change 25/05/2017 14:52