CODE 60083 ACADEMIC YEAR 2022/2023 CREDITS 9 cfu anno 2 ECONOMIA AZIENDALE 8697 (L-18) - GENOVA 9 cfu anno 2 ECONOMIA E COMMERCIO 8699 (L-33) - GENOVA 9 cfu anno 2 ECONOMIA DELLE AZIENDE MARITTIME, LOGISTICA E TRASP. 8698 (L-18) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR SECS-S/01 LANGUAGE Italian TEACHING LOCATION GENOVA SEMESTER 2° Semester SECTIONING Questo insegnamento è diviso nelle seguenti frazioni: A B C PREREQUISITES Propedeuticità in ingresso Per sostenere l'esame di questo insegnamento è necessario aver sostenuto i seguenti esami: Business Administration 8697 (coorte 2021/2022) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 D CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 B CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 C CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 A Maritime, Logistics and Transport Economics and Business 8698 (coorte 2021/2022) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 D CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 B CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 C CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 A Economics 8699 (coorte 2021/2022) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 D CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 B CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 C CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 A Propedeuticità in uscita Questo insegnamento è propedeutico per gli insegnamenti: Economics 8699 (coorte 2021/2022) STATISTICS 1 60083 2021 TEACHING MATERIALS AULAWEB OVERVIEW 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. AIMS AND CONTENT LEARNING OUTCOMES 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. AIMS AND LEARNING OUTCOMES 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 representations; carry out basic descriptive analyses for univariate phenomena; analyze the relationships between two or more phenomena with particular emphasis on association 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 non-statisticians. Learning skills: Students will develop adequate learning skills that allow them to continue to study the subject independently. Connections of the course with other courses in the programme: The topics introduced in this course will allow the students to properly understand numerical data within other disciplines and will put the bases to study and analyze quantitative methods in other quantitative courses. PREREQUISITES The course requires knowledge of the basic skills of a course of General Mathematics for Business and/or Economics. TEACHING METHODS 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). SYLLABUS/CONTENT Part I: Elements of descriptive statistics Introduction to data collection Distribution of a variable and its representation: Frequency distributions and diagrams Location indices: means, median, mode, percentiles Scale indices Measures of concentration Association measures for two variables Statistical independence Association between qualitative variables. Correlation between quantitative variables Simple linear regression Part II: Probability Events and events sigma-field Kolmogorov axioms Conditional probability and independence Bayes theorem Discrete and continuous random variables: Bernoulli and Binomial r.v. Poisson r.v. Normal r.v. The Central Limit Theorem Part III: Introduction to statistical inference Sampling and sampling distributions Point estimation Estimators and their properties Interval estimation Confidence interval for a mean (variance unknown) Confidence interval for a proportion Theory of statistical Test for a mean, test for a proportion. Comparison of two means. RECOMMENDED READING/BIBLIOGRAPHY Foreign students are asked to contact the teachers to agree on the text book in English language. TEACHERS AND EXAM BOARD MARTA NAI RUSCONE Ricevimento: It is possible to arrange a meeting with the lecturer by sending an email to email@example.com Exam Board MARTA NAI RUSCONE (President) DANIELE DE MARTINI FABIO RAPALLO LESSONS LESSONS START Classes will start in the first week of the second semester according to the calendar of the Department of Economics. Class schedule STATISTICS 1 C EXAMS EXAM DESCRIPTION The examination consists of a written test which includes: 1) multiple-choice questions of a theoretical nature. 2) theoretical questions with open answers 3) exercises The examination regulations are published on the course's Aulaweb page. As a result of the COVID 19 pandemic, the examination procedures may change in relation to the University regulations. ASSESSMENT METHODS The questions and exercises in the written exam 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. The details on the exam preparation and the required level of detail for all the topics will be illustrated during the lectures. Exam schedule Data Ora Luogo Degree type Note 17/01/2023 09:30 GENOVA Scritto 31/01/2023 09:30 GENOVA Scritto 14/02/2023 09:30 GENOVA Scritto 11/05/2023 14:30 GENOVA Scritto Appello straordinario riservato esclusivamente ai laureandi a.a. 2021/22 13/06/2023 09:30 GENOVA Scritto 27/06/2023 09:30 GENOVA Scritto 11/07/2023 09:30 GENOVA Scritto 12/09/2023 09:30 GENOVA Scritto FURTHER INFORMATION Additional information for non-attending students For non-attending students, no program changes or assessment procedures are applied.