DATA ANALYSIS

Academic year
2021/2022 Syllabus of previous years
Official course title
DATA ANALYSIS
Course code
ET2005 (AF:304901 AR:171274)
Modality
On campus classes
ECTS credits
6
Degree level
Bachelor's Degree Programme
Educational sector code
SECS-S/05
Period
3rd Term
Course year
3
Moodle
Go to Moodle page
The course is one of the interdisciplinary activities of the three-year degree course in Business Economics and Management that allows students to acquire the knowledge and understanding of some of the main statistical concepts and their use in administrative and business management activities. The aim of the course is to provide students with skills that allow them to view, extract and interpret information from sample surveys and available databases to plan strategies to support decision making.
Frontal lectures, the study and analysis of the reference texts and the suggested materials, will allow students to:

1. Knowledge and understanding
1.1 know the terminology and basic principles of descriptive and inferential statistics of analysis of business phenomena

2. Ability to apply knowledge and understanding
2.1 know how to extract, interpret and communicate information originating from sample surveys and available databases
2.2 understand the main aspects of the descriptive and inferential statistical analyses
2.3 know how to choose and apply statistical models for the analysis and prediction of business phenomena

3. Making judgements
3.1 be able to critically assess the reliability of the assumptions underlying the analyzes carried out
3.2 be able to assess the goodness of the models proposed and the results achieved

4. Communication
4.1 know how to present information extracted from sample surveys and available databases
4.2 be able to successfully analyze the proposed models and the results achieved

Statistics, in particular students should be able to handle basics of descriptive and inferential statistics
During the course the following topics will be analyzed:

1. Sample surveys: basics, surveys techniques, measurement error
2. Refesh inferential statistics: point estimation and hypothesis testing
3. The analysis of dependence: simple regression
4. The analysis of dependence: multiple regression

In order to support the theoretical knowledge acquired during the course, each theme may be developed also through the use of the statistical software R.
- On-line material available in the moodle Platform from the course web site
- Book
in English: Hermann C, Schomaker M, Shalabh. Introduction to Statistics and Data Analysis. Springer, 2016
in Italian: Paganoni A.M., Ieva F. and Vitelli V. (2016). Laboratorio di statistica con R, 2 edizione, Pearson
The verification of learning takes place through a written test
Conventional
English
written
This programme is provisional and there could still be changes in its contents.
Last update of the programme: 06/08/2021