CODE  60083 

ACADEMIC YEAR  2022/2023 
CREDITS 

SCIENTIFIC DISCIPLINARY SECTOR  SECSS/01 
LANGUAGE  Italian 
TEACHING LOCATION 

SEMESTER  2° Semester 
SECTIONING  This unit is divided into 3 sections: 
PREREQUISITES 
Prerequisites
You can take the exam for this unit if you passed the following exam(s):
Prerequisites (for future units)
This unit is a prerequisite for:

TEACHING MATERIALS  AULAWEB 
The course “Statistics 1” aims to provide students with the main tools for the quantitative analysis of economic and social phenomena, and to supply the basic statistical knowledge needed to face the other quantitative courses of the Degree Programme.
The main aim of the course is to provide students with the fundamental tools of descriptive and inferential statistical analysis. The first part  Elements of descriptive statistics  relates to the fundamental concepts of univariate and bivariate descriptive statistics and is essential for any subsequent study. The second part  Introduction to probability theory  is designed to present the basic ideas needed for the study of statistical inference. The third part  Introduction to statistical inference  addresses the fundamental issues of sampling and inference, with particular regard to the theory of estimation and hypothesis testing.
Knowledge and understanding: Students will know the main tools used to summarize the information and for the generalization of the information observed through sample surveys.
Ability to apply knowledge and understanding: Students will be able to reorganize data in univariate and bivariate frequency tables providing adequate graphical representation; carry out basic descriptive analyses for onedimensional phenomena; analyze the relationships between two or more phenomena with particular emphasis on dependence and linear regression analysis. They will also be able to apply some statistical inference tools to solve simple problems.
Making judgements: Students must be able to use the acquired knowledge both on a theoretical and operational level with autonomous assessment skills, in various applicative contexts.
Communication skills: Students will acquire the technical language typical of the discipline to communicate clearly and without ambiguity with both statisticians and nonstatisticians.
Learning skills: Students will develop adequate learning skills that allow them to continue to study the subject independently.
The course requires knowledge of the basic contents of a course of General Mathematics for Business and Economics.
Traditional lessons and exercises and through AulaWeb. Since the training objectives concern both theoretical and applicative skills, there will be both lessons focused on the methodological aspects of statistics and lessons based on exercises in which numerical problems are faced and examples of simple analyzes on real data are discussed.
Due to the Covid19 pandemic, students will be informed via email and AulaWeb messages on the actual method of the lessons (in person or remotely).
Part I: Elements of descriptive statistics
Part II: Probability
Part III: Introduction to statistical inference
Foreign students are asked to contact the teachers to agree on the text book in English language.
DANIELE DE MARTINI (President)
MARTA NAI RUSCONE
FABIO RAPALLO
Classes will start in the first week of the second semester according to the calendar of the Department of Economics.
The . Because of the COVID 19 pandemics exam rules could change
L'esame consiste in una prova scritta. A seguito della pandemia COVID 19 le modalità d'esame potrebbero cambiare in relazione ai regolamenti di Ateneo. Il regolamento d'esame è pubblicato sulla pagina Aulaweb del corso.
The written examination consists of:
1) multiplechoice questions of a theoretical nature.
2) theoretical questions with open answers
3) exercises
The questions and exercises are chosen to cover, as far as possible, all the topics of the program. The theoretical questions are used to assess the student's level of understanding, while the exercises are used to measure the ability to apply the acquired knowledge.
Attendance 
Optional  6 lecture hours/week in Italian 