Insegnamento a.a. 2017-2018



Department of Decision Sciences

Course taught in English

Go to class group/s: 19
ACME (6 credits - I sem. - OB  |  3 credits SECS-S/01  |  3 credits SECS-S/06)
Course Director:

Classes: 19 (I sem.)

Course Objectives

This course is designed to develop students' knowledge and skills as users of quantitative data to support management decision making. After completing the course, students are able to prepare accurate and informative data summaries for inclusion in management reports and to contribute to the commissioning and interpretation of reports of business research. Moreover, they are aware of some of the main statistical techniques that can be used to support management decision making.
The course takes a user-oriented, an applied approach to use publicly available data, surveys, and statistical methods, to improve understanding of management issues, and to plan and evaluate events, activities and programs. Calculations are performed using SPSS, with an emphasis on effective use of the software and interpretation of results. All lectures include sessions of students independent work with the computer.

Intended Learning Outcomes
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Course Content Summary

  • Business research processes and business analytics.
  • Introduction to the use of SPSS for data management and data analysis.
  • Advanced techniques of data analysis: multivariate linear regression, logistic regressions and factor analysis.

Teaching methods
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Assessment methods
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Detailed Description of Assessment Methods

For attending students
  • Four tests. Students are asked to answer questions through Blackboard platform, on the basis of the results of a data analysis with SPSS. Each test is graded out of 31. The arithmetic average of the test grades contributes 70% to the final mark.
  • In-class marked activities graded out of 31. The in-class activities contribute 30% to the final mark.

For non attending students
  • One final general written exam, with open ended questions to be answered on the basis of the results of a data analysis with SPSS, using all the techniques introduced in the course. The general exam is graded out of 31.


There are no partial exams.


  • R. GRAZIANI, M. ANGELICI, Lectures notes on Multivariate Statistical Analyses with SPSS.
  • Slides of the course, delivered through Blackboard platform for E-learning.
  • R. TARLING, Statistical Modelling for Social Researchers. Principles and practice, London and New York, Routledge, 2009, (Additional Readings).

Exam textbooks & Online Articles (check availability at the Library)
Last change 16/05/2017 09:59