Course 2017-2018 a.y.

Classes: 19 (I sem.)

Instructors:
Class 19: REBECCA GRAZIANI

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.

• 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.
  

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).