COMPUTING SKILLS FOR ECONOMICS
- Academic year
- 2019/2020 Syllabus of previous years
- Official course title
- ELEMENTI DI INFORMATICA PER L'ECONOMIA
- Course code
- ET0032 (AF:313266 AR:167467)
- Modality
- On campus classes
- ECTS credits
- 6
- Subdivision
- Surnames Lb-Z
- Degree level
- Bachelor's Degree Programme
- Educational sector code
- SECS-S/01
- Period
- 4th Term
- Course year
- 1
- Where
- TREVISO
- Moodle
- Go to Moodle page
Contribution of the course to the overall degree programme goals
The course is one of the activities of the degree course in Economics that allows students to improve knowledge for data management through ad-hoc software and for reporting. The aim of the course is to provide the basic informatic knowledge in order to let students develop the skills to structure, process, analyse data, disclose information using informatic tools. To this goal the students will be introduced to R software and reporting techniques.
Expected learning outcomes
- Knowledge and understanding
- To know the basic computer terminology for both the hardware and software
- To to recognize the logical-formal structure of a problem
- Ability to apply knowledge and understanding
- To use basic terminology correctly
- To formalize a problem by constructing a suitable algorithm
- To use dedicated software for the analysis of economic-business data
- Making judgements
- To apply the computerized procedures during the economic decision process.
- To know the basic computer terminology for both the hardware and software
- To to recognize the logical-formal structure of a problem
- Ability to apply knowledge and understanding
- To use basic terminology correctly
- To formalize a problem by constructing a suitable algorithm
- To use dedicated software for the analysis of economic-business data
- Making judgements
- To apply the computerized procedures during the economic decision process.
Pre-requirements
Fulfillment of OFAs (Additional Learning Requirements). Students must know the fundamental of Mathematics even without passing the exam.
Contents
Part I - From problems to solutions
- Defining the problem and identification of variables
- Encoding of a problem in pseudo-code
- Conditional expressions
- Cycles "for" and "while”
- Implementation of a pseudo code
Part II - Introduction to the use of spreadsheets and the R language
- Data collection and their organization in data-sheet with Excel
- The tabular representation of one or more detected variables
- Graphical representation of data sets and reporting
- Defining the problem and identification of variables
- Encoding of a problem in pseudo-code
- Conditional expressions
- Cycles "for" and "while”
- Implementation of a pseudo code
Part II - Introduction to the use of spreadsheets and the R language
- Data collection and their organization in data-sheet with Excel
- The tabular representation of one or more detected variables
- Graphical representation of data sets and reporting
Referral texts
Statistica e calcolo con R (2015) E. Loli Piccolomini, A. Messina edizione McGraw-Hill Education (Italy) versione e-book cap. 1, 2, 3, 8 e Appendici A e B
Letture integrative
- Dispense, lucidi e altro materiale disponibile sulla piattaforma di e-learning moodle.unive.it.
- Elementi di Informatica per l’Economia, Custom
Publishing, F. Luccio, McGraw-Hill Create, capp. 1, 2.
Letture integrative
- Dispense, lucidi e altro materiale disponibile sulla piattaforma di e-learning moodle.unive.it.
- Elementi di Informatica per l’Economia, Custom
Publishing, F. Luccio, McGraw-Hill Create, capp. 1, 2.
Assessment methods
The method that will be used to assess the knowledge and skills acquired is written exam by moodle platform.
The written exam will consist of two parts:
- a first part with 15 multiple-choice items as barrier in order to test the mastery of a minimum set of basic knowledge. Students who correctly answer at least 10 questions will be admitted to the second part.
- a second part of 2 practical exercises both to test the acquirement of the topics presented during the lessons and the familiarity with R.
The two tests will weigh 50% in the final evaluation.
The written exam will consist of two parts:
- a first part with 15 multiple-choice items as barrier in order to test the mastery of a minimum set of basic knowledge. Students who correctly answer at least 10 questions will be admitted to the second part.
- a second part of 2 practical exercises both to test the acquirement of the topics presented during the lessons and the familiarity with R.
The two tests will weigh 50% in the final evaluation.
Teaching methods
The course consists of frontal lessons, using R software to analize data and teaching modules available on the moodle.unive.it e-learning platform.
Students must register for the moodle platform and computer will be required during the lessons.
Students must register for the moodle platform and computer will be required during the lessons.
Type of exam
written
Definitive programme.
Last update of the programme: 11/10/2019