CODE 60083 ACADEMIC YEAR 2024/2025 CREDITS 9 cfu anno 2 ECONOMIA AZIENDALE 8697 (L-18) - GENOVA 9 cfu anno 2 ECONOMIA DELLE AZIENDE MARITTIME, LOGISTICA E TRASP. 8698 (L-18) - GENOVA 9 cfu anno 2 SCIENZE ECONOMICHE E FINANZIARIE 11662 (L-33) - 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 2023/2024) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 A CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 B CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 C Maritime, Logistics and Transport Economics and Business 8698 (coorte 2023/2024) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 A CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 B CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 C Economics 8699 (coorte 2023/2024) CALCULUS FOR UNDERGRADUATED STUDENTS. 41138 2023 Propedeuticità in uscita Questo insegnamento è propedeutico per gli insegnamenti: Economics 8699 (coorte 2023/2024) ECONOMETRICS 24615 TEACHING MATERIALS AULAWEB OVERVIEW The Statistics 1 course aims to equip students with the main tools for the quantitative analysis of economic and social phenomena and lay the necessary foundations to tackle the other quantitative courses of the Course of Studies. 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 for synthesizing information and generalizing what is 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 analyzes for one-dimensional phenomena, analyze the relationships between two or more phenomena with particular reference to the dependence and linear regression analysis. They will also be able to apply some statistical inference tools to solve simple problems. Independence of judgement: Students must be able to use the knowledge acquired both on a conceptual and operational level with independent evaluation ability and ability in different application contexts. Communication skills: Students will acquire the technical language typical of the discipline to communicate clearly and unambiguously with specialist and non-specialist interlocutors. Learning skills: Students will develop adequate learning skills that allow them to continue to explore the subject independently. PREREQUISITES The teaching presupposes knowledge of the basic contents of a course in General Mathematics for economic or business degree courses. TEACHING METHODS Lessons and exercises. Since the training objectives concern both theoretical and applicative skills, the lessons in which the methodological aspects of statistics are presented will be alternated with exercises in which numerical problems and examples of simple analyzes on real data are addressed. Students who have valid certification of physical or learning disabilities and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Serena Scotto (scotto@economia.unige.it), the Department’s disability liaison. SYLLABUS/CONTENT Part I: Descriptive statistics Introduction to statistics. Descriptive and inferential statistics. Populations and samples. Distributions, frequencies, and cumulative frequencies. Graphs to describe categorical variables, time series, and quantitative variables. Graphs and tables to describe relationships between variables. Location measures: mean, median, mode, percentiles. Variability measures. Box-plot. Measures of concentration. Measures of relationships between variables. Part II: Probability Random experiments, outcomes, events. The probability function and its axioms. Rules of probability. Conditional probability and independence. Bivariate probabilities. Bayes’ theorem. Discrete random variables and their properties. Bernoulli, Binomial, Poisson distributions. Continuous random variables and their properties. Uniform and normal distributions. Joint distributions. Part III: Inference Sampling and sampling distributions. Distribution of the sample mean. The central limit theorem. Distribution of the sample proportion. Point estimation. Estimators and their properties. Confidence intervals. Confidence intervals for the mean and for the proportions. Confidence interval for a proportion Theory of statistical hypothesis testing. Test for a mean, test for a proportion. Comparison of two means. Part IV: Relationships between variables Correlations and linear regression. The simple linear regression model. Least squares technique least squares coefficient estimators. The explanatory power of a linear regression equation. Inference on the coefficients. Statistical independence and chi-square test. RECOMMENDED READING/BIBLIOGRAPHY "Statistica"; Newbold, Carlson, Thorne, Nona edizione, ed. Pearson (2021). Per gli studenti stranieri è possibile fare riferimento al testo originale in lingua inglese. "Introduzione alla statistica inferenziale - per le scienze economiche e aziendali"; D. De Martini, ed. Esculapio (2024). TEACHERS AND EXAM BOARD DANIELE DE MARTINI Ricevimento: See the course webpage on aulaweb. Exam Board DANIELE DE MARTINI (President) MARTA NAI RUSCONE FABIO RAPALLO LESSONS LESSONS START Lessons begin in the first week of the second semester as per the Department teaching calendar. Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The examination consists of a written test. An additional discussion may be requested at the discretion of the examination committee. ASSESSMENT METHODS The written exam consists of: 1) multiple choice theoretical questions 2) open-ended theoretical questions 2) exercises The questions and exercises are chosen so as to cover, as far as possible, all the topics of the exam programme. The theoretical questions are used to evaluate the student's level of understanding, while the exercises are used to measure the ability to apply the knowledge acquired. Exam schedule Data appello Orario Luogo Degree type Note 17/12/2024 09:30 GENOVA Scritto + Orale con accettazione online 15/01/2025 09:30 GENOVA Scritto + Orale con accettazione online 29/01/2025 09:30 GENOVA Scritto + Orale con accettazione online 27/05/2025 09:30 GENOVA Scritto + Orale con accettazione online 11/06/2025 09:30 GENOVA Scritto + Orale con accettazione online 09/07/2025 09:30 GENOVA Scritto + Orale con accettazione online 12/09/2025 09:30 GENOVA Scritto + Orale con accettazione online