DATA ANALYSIS

Academic year
2018/2019 Syllabus of previous years
Official course title
DATA ANALYSIS
Course code
ET2005 (AF:241181 AR:130920)
Modality
On campus classes
ECTS credits
6
Degree level
Bachelor's Degree Programme
Educational sector code
SECS-S/05
Period
2nd 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
Knowledge of the basic concepts of descriptive and inferential statistics.
During the course the following topics will be analyzed:

1. Extraction of information from sample surveys and databases
2. Summary statistics, frequency tables and graphical representations of the available information
3. Linear and non linear statistical models

In order to support the theoretical knowledge acquired during the course, each theme will be developed through the use of the statistical software R.
Slides, data and all the reference material needed to follow the course and achieve the expected learning outcomes are available on the e-learning platform moodle.unive.it

Dalgaard Peter. Introductory statistics with R, 2008, Springer.
The verification of learning takes place through a written test. Students will be asked to analyze a set of data and to answer some questions in order to verify the mastery of a minimum set of basic knowledge and the skills acquired in the elaboration, interpretation, analysis and communication of available information.

During the written test, the use of R software is allowed.
The course consists of lectures to introduce various statistical methods for organizing, visualizing, and analysing information available through sample surveys and available databases.
The methods and models analyzed will be discussed and illustrated through the statistical software R (www.r-project.org).
English
Students should to register on the course page of the e-learning platform moodle.unive.it

Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments

Ca' Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.
written
Definitive programme.
Last update of the programme: 08/07/2018