ITA | ENG
B028396 - Workshop in data analysis
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Further information
Type of Assessment
Course program
Academic Year 2022-23
Course year
Third year - Second Semester
Belonging Department
Economics and Management (DISEI)
Course Type
Single education field course
Scientific Area
SECS-S/03 - ECONOMIC STATISTICS
Credits
3
Teaching Hours
24
Teaching Term
20/02/2023 ⇒ 01/06/2023
Attendance required
No
Type of Evaluation
Giudizio Finale
Course Content
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Course program
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Lectureship
Mutuality
Course teached as:
B028396 - LABORATORIO DI ANALISI DATI
3-years First Cycle Degree (DM 270/04) in ECONOMICS AND TRADE
Curriculum ECONOMICS
B028396 - LABORATORIO DI ANALISI DATI
3-years First Cycle Degree (DM 270/04) in ECONOMICS AND TRADE
Curriculum ECONOMICS
Teaching Language
Italian.
Course Content
Introduction to the software R. Descriptive analysis. Regression models. Time series analysis models
Suggested readings (Search our library's catalogue)
Lecture material will be posted on the Moodle class web page.
Lecture notes on R are freely available on the website https://cran.r-project.org/.
Information on manuals that use R for statistical analysis will be provided during the lab sessions.
Lecture notes on R are freely available on the website https://cran.r-project.org/.
Information on manuals that use R for statistical analysis will be provided during the lab sessions.
Learning Objectives
The objective of the course is to provide basic knowledge and skills in the statistical analysis of data using the R software. The lab sessions aim to apply the methods presented in the previous statistical courses and highlight the operational problems connected with applications on actual data.
The objectives of knowledge and understanding and the ability to apply knowledge and understanding are the following.
Knowledge and understanding: Know and understand the operational basics of the software R.
Application of knowledge and understanding: The student must be able to apply the statistical analysis procedures presented autonomously and interpret the results, paying particular attention to the nature and reliability of the data analyzed and to the potential and limitations of the models and methods used.
The objectives of knowledge and understanding and the ability to apply knowledge and understanding are the following.
Knowledge and understanding: Know and understand the operational basics of the software R.
Application of knowledge and understanding: The student must be able to apply the statistical analysis procedures presented autonomously and interpret the results, paying particular attention to the nature and reliability of the data analyzed and to the potential and limitations of the models and methods used.
Prerequisites
It is assumed that students are familiar with basic descriptive and inferential statistics. Furthermore, knowledge of the statistical methods provided in the “Introduction to Econometrics” and “Economic Statistics” courses is required.
Teaching Methods
The course includes classroom lectures with computer work sessions concerning the application of statistical procedures with R.
Further information
To access the Moodle class web page, students must send an e-mail request to the teacher. The e-mail must be sent from the institutional UNIFI address.
Type of Assessment
The exam consists of an oral examination with a discussion of the homeworks (in the form of R scripts) assigned during the course.
Course program
R environment. Numbers, vectors, matrices, dataframes. Packages and libraries. Reading in data from external files. Descriptive statistical analysis. Graphical procedures. Statistical models in R. Estimation of simple and multiple regression models. Time series models: composition / decomposition models, ARIMA models.