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STATISTICS 1

CODE 60083
ACADEMIC YEAR 2022/2023
CREDITS
  • 9 cfu during the 2nd year of 8697 ECONOMIA AZIENDALE(L-18) - GENOVA
  • 9 cfu during the 2nd year of 8699 ECONOMIA E COMMERCIO(L-33) - GENOVA
  • 9 cfu during the 2nd year of 8698 ECONOMIA DELLE AZIENDE MARITTIME, LOGISTICA E TRASP.(L-18) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR SECS-S/01
    LANGUAGE Italian
    TEACHING LOCATION
  • GENOVA
  • 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):
    • Business Administration 8697 (coorte 2021/2022)
    • CALCULUS FOR UNDERGRADUATED STUDENTS. 41138
    • Maritime, Logistics and Transport Economics and Business 8698 (coorte 2021/2022)
    • CALCULUS FOR UNDERGRADUATED STUDENTS. 41138
    • Economics 8699 (coorte 2021/2022)
    • CALCULUS FOR UNDERGRADUATED STUDENTS. 41138
    Prerequisites (for future units)
    This unit is a prerequisite for:
    • Economics 8699 (coorte 2021/2022)
    • ECONOMETRICS 24615
    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

    1. Introduction to data collection
    2. Distribution of a variable and its representation: Frequency distributions and diagrams
    3. Location indices: means, median, mode, percentiles
    4. Scale indices
    5. Measures of  concentration
    6. Association measures for two variables
    7. Statistical independence
    8. Association between qualitative variables.
    9. Correlation between quantitative variables
    10. Simple linear regression

    Part II: Probability

    1. Events and events sigma-field
    2. Kolmogorov axioms
    3. Conditional probability and independence
    4. Bayes theorem
    5. Discrete and continuous random variables:
      1. Bernoulli and Binomial r.v.
      2. Poisson r.v.
      3. Normal r.v.
    6. The Central Limit Theorem

    Part III: Introduction to statistical inference

    1. Sampling and sampling distributions
    2. Point estimation
    3. Estimators and their properties
    4. Interval estimation
    5. Confidence interval for a mean (variance unknown)
    6. Confidence interval for a proportion
    7. Theory of statistical
    8. Test for a mean, test for a proportion.
    9. 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

    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

    Date Time Location Type Notes
    17/01/2023 09:30 GENOVA Scritto
    31/01/2023 09:30 GENOVA Scritto
    14/02/2023 09:30 GENOVA Scritto
    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.