Insegnamento a.a. 2015-2016

20149 - QUANTITATIVE METHODS FOR MANAGEMENT


ACME

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:
REBECCA GRAZIANI

Classes: 19 (I sem.) - 19 (I sem.) - 19 (I sem.)
Instructors:
Class 19: REBECCA GRAZIANI, Class 19: TO BE DEFINED, Class 19: TO BE DEFINED



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. 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, 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 software such as SPSS, with an emphasis on effective use of the software and interpretation of results. All lectures are held in the IT room and include sessions of students independent work.


Course Content Summary

  • Business research processes and research design.
  • Data collection: different approaches, measurement, design, sampling. Examples.
  • Data analysis: basic ideas, representations.
  • Data analysis: applied multivariate techniques, namely multivariate linear regression, logistic regressions and factorial analysis.

Detailed Description of Assessment Methods

    The assessment method is different for attending and not attending students.

Textbooks

  • Lecture notes
  • R. TARLING, Statistical Modelling for Social Researchers. Principles and practice, London and New York, Routledge, 2009.

Exam textbooks & Online Articles (check availability at the Library)
Last change 18/05/2015 15:41