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CODE 60083
ACADEMIC YEAR 2024/2025
CREDITS
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:
    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

    1. Introduction to statistics. Descriptive and inferential statistics. Populations and samples.
    2. Distributions, frequencies, and cumulative frequencies. Graphs to describe categorical variables, time series, and quantitative variables. Graphs and tables to describe relationships between variables.
    3. Location measures: mean, median, mode, percentiles.
    4. Variability measures. Box-plot. Measures of  concentration.
    5. Measures of relationships between variables.

    Part II: Probability

    1. Random experiments, outcomes, events.
    2. The probability function and its axioms. Rules of probability.
    3. Conditional probability and independence. Bivariate probabilities.
    4. Bayes’ theorem.
    5. Discrete random variables and their properties.
    6. Bernoulli, Binomial, Poisson distributions.
    7. Continuous random variables and their properties.
    8. Uniform and normal distributions.
    9. Joint distributions.

    Part III: Inference

    1. Sampling and sampling distributions.
    2. Distribution of the sample mean. The central limit theorem. Distribution of the sample proportion.
    3. Point estimation. Estimators and their properties.
    4. Confidence intervals. Confidence intervals for the mean and for the proportions.
    5. Confidence interval for a proportion
    6. Theory of statistical hypothesis testing. Test for a mean, test for a proportion.
    7. Comparison of two means.

    Part IV: Relationships between variables

    1. 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.
    2. 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

    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