WORKSHOP ON STATISTICS FOR ECONOMICS

The course is an activity useful to improve the skills for statistical data management of an Economics degree course through ad-hoc software and for reporting. In particular, software R will be introduced to students.
The aim of the course is to provide data analysis and management knowledge in order to improve the skills to analyse data and disclose information using informatic tools.
The students will use softwares R and RStudio through real application (i.e. with business data) and to reporting techniques.

Frontal lectures and laboratory will allow students:

1. Knowledge and understanding
1.1 to know and use software for the analysis of economic phenomena.
2. Ability to apply knowledge and understanding
2.1 to organize economic-business data related to the markets and businesses applying dedicated software
2.2 to synthesize economic data
3. Making judgements
3.1 to apply critically the different procedures in the economic decision and in the management of uncertainty.

To have achieved the learning outcomes of the Statistics. In particular, the student should master the concepts and methods related to basic inference and descriptive Statistics, that are p-value, confidence intervals, frequency distributions, main indices of a distribution and graphical representation.

1-Introduction to R: Student will learn how to use the software R focusing in particular on loading data and handling variables
2- Use of markup language: Rmarkdown, through RStudio
3- Starting from real data, students will learn how to build graphical and tabular representations to get meaningful synthesis of the examined phenomenon
4-It will be shown the implementation of some fundamental inferential tools (point estimation, confidence intervals, tests) with real data
5-Linear regression and some multivariate analysis techniques to synthesize economic data

Statistica e calcolo con R (2015) E. Loli Piccolomini, A. Messina McGraw-Hill Education (Italy) eds., e-book caps 3, 4, 5, 6 and Appendix A and B
- On-line material in moodle.unive.it area (notes of the teacher, slides and other materials)
- Faraway J. (2004). Linear Models with R. CRC Press.

To assess the knowledge and skills acquired during the laboratory activity, a statistical analysis of the data will be presented by the student with the support of the same R program. In this phase, the skills of argumentative and critical analysis will be evaluated.
In particular, the exam aims to verify that the student has acquired the concepts presented during the lessons, is familiar with R software and may solve and present some practical business problems.
To this end the student will be asked to analyze a dataset and to present it using R and its additional packages.

written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

Assessment criteria:
A. Marks from 18 to 21 are awarded if the student demonstrates that they have acquired basic knowledge of data analysis through the use of dedicated software.
B. Marks from 22 to 26 are awarded if the student demonstrates that they are able to prepare, in R, a report that provides a satisfactory summary of the collected data through graphs and tables.
C. Marks from 27 to 30 are awarded if the student demonstrates that they are able to prepare, in R, a report that provides a good summary of the collected data through graphs, tables, and statistical models.
D. Honours will be awarded if the student demonstrates an excellent ability to analyze data by proposing a summary that makes use of all the tools learned during the course.

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.

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.