Introduction à la statistique I

  • Teaching

    Details

    Faculty Faculty of Management, Economics and Social Sciences
    Domain Information Systems
    Code UE-EIG.00122
    Languages French
    Type of lesson Lecture
    Level Bachelor
    Semester AS-2024

    Schedules and rooms

    Summary schedule Wednesday 08:15 - 12:00, Hebdomadaire, ONL, Room Online (Autumn semester)
    Hours per week 3

    Teaching

    Responsibles
    • Donzé Laurent
    Teachers
    • Donzé Laurent
    Assistants
    • Rosset Julien
    Description

    This course is the first part of an education program in Statistics. It has to be followed by all the Faculty's students. Contents and difficulty degree of this basic introduction correspond to a standard international level.

    The course is a descriptive and no formal introduction to Statistics:

    1. Introduction (Population and statistical unit; variables)
    2. Empirical distributions (Categorical variables; quantitative variables;  histogram and cumulated empirical distributions; estimation of empirical distributions by kernel functions; shapes of distribution functions)
    3. Characterisation of distribution functions (Measures of location; measures of dispersion; measures of symmetry and kurtosis; Lorenz curve and Gini concentration index; normal distribution; qq-plot and normal probability plot)
    4. Probability and statistical inference (Probability; random variables and probability laws; statistical inference and confidence interval)

    Especially, the concepts of distribution, probability, confidence intervals, and hypotheses tests will be treated. The course is illustrated by economic, demographic or social statistical examples.

    For a better understanding and a broader look at the taught subjects, exercises are provided. In parallel, students have to participate in an online SPSS workshop.

    SPSS workshop

    The SPSS workshop gives students an introduction to the SPSS software. The aim is to familiarise with the software, to do simple manipulations and to use it in elementary statistical analyses. The workshop is an online course and proposes a self-learning method. The main features are given by video clips, which explain several manipulations through the menu in order to solve some concrete cases.

    Moodle

    Training objectives

    As the emphasis is given on the tools of the Descriptive Statistics, the student will be able at the end of the course to produce a descriptive analysis of data, and in particular to describe and comment and empirical distribution, and to test hypotheses on the mean of a distribution.

    Condition of access

    Registered students at the University with a Federal maturity or an equivalent diploma.

    Comments

    Only students who will have validated the course could write a Seminar thesis under the supervision of the professor.

    Softskills Yes
    Softskills seats 20
    Off field No
    BeNeFri Yes
    Mobility Yes
    UniPop No
    Auditor Yes

    Documents

    Bibliography

    A script with a listing of references is provided. The student will find on the course's Moodle platform other resources.

    Files and attachments
  • Dates and rooms
    Date Hour Type of lesson Place
    18.09.2024 08:15 - 12:00 Cours PER 21, Room G120
    25.09.2024 08:15 - 12:00 Cours PER 21, Room G120
    02.10.2024 08:15 - 12:00 Cours PER 21, Room G120
    09.10.2024 08:15 - 12:00 Cours PER 21, Room G120
    16.10.2024 08:15 - 12:00 Cours PER 21, Room G120
    23.10.2024 08:15 - 12:00 Cours PER 21, Room G120
    30.10.2024 08:15 - 12:00 Cours PER 21, Room G120
    06.11.2024 08:15 - 12:00 Cours PER 21, Room G120
    13.11.2024 08:15 - 12:00 Cours PER 21, Room G120
    20.11.2024 08:15 - 12:00 Cours PER 21, Room G120
    27.11.2024 08:15 - 12:00 Cours ONL, Room Online
    04.12.2024 08:15 - 12:00 Cours PER 21, Room G120
    11.12.2024 08:15 - 12:00 Cours PER 21, Room G120
    18.12.2024 08:15 - 12:00 Cours PER 21, Room G120
  • Assessments methods

    Written exam - AS-2024, Session d'hiver 2025

    Date 08.01.2025 14:00 - 15:30
    Assessments methods By rating
    Descriptions of Exams

    Durée d'examen: 90 min.
    La participation à l'atelier SPSS et la réussite de l'atelier sont obligatoires pour la participation à l'examen.

    Written exam - SS-2025, Session de rattrapage 2025

    Date 20.08.2025 08:30 - 10:00
    Assessments methods By rating
    Descriptions of Exams

    Durée d'examen: 90 min.
    La participation à l'atelier SPSS et la réussite de l'atelier sont obligatoires pour la participation à l'examen.

  • Assignment
    Valid for the following curricula:
    Ba - Business Informatics - 180 ECTS
    Version: 2020-SA_V02
    1st year 60 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    Ba - Communication Studies - 90 ECTS
    Version: 2023-SA_V01
    1st year - 36 ECTS > Introduction à la statistique I / Einführung in die Statistik I
    2nd and 3rd year - 54 ECTS > Course - 39ECTS > Elective courses - 15 ECTS > Elective courses of the SES Faculty > Elective BA courses SES max 4.5

    Ba - Communication and Media Research - 120 ECTS
    Version: 2021-SA_V04
    1st year - 42 ECTS

    Ba - Economics - 180 ECTS
    Version: 2018-SA_V03
    1st year 60 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    Ba - Management - 180 ECTS
    Version: 2019-SA_V02
    1st year 60 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    Ba - Management - 180 ECTS
    Version: 2018-SA_V02
    1st year 60 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    Ba - Management and Economics - 120 ECTS
    Version: 2018-SA_V02
    1st year - 42 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    BcBa - Kommunikationswissenschaft und Medienforschung - 60 ECTS
    Version: 2021-SA_V02
    Wahlvorlesungen - mind. 18 ECTS > Introduction à la statistique I / Einführung in die Statistik I

    BeNeFri - Sciences économiques et sociales
    Version: 2018-SP_V01 - SES BeNeFri
    Course > Bachelor course offering for BeNeFri Students

    Complementary learnings in SES or mobility students
    Version: ens_compl_ses
    Bachelor course offering for Mobility Students

    Education / Psychology 120
    Version: SA20_BA_bil_v01
    BP1.7-B Bereichsübergreifende Kompetenzen / Compétences transversales

    Education / Psychology 120
    Version: SA14_BA_fr_v02
    CTC / BP1.8-F

    Education / Psychology 120
    Version: SA20_BA_de_v01
    BP1.7-D Bereichsübergreifende Kompetenzen

    Educational Sciences 120
    Version: SA20_BA_bil_v01
    Variante A > BE1.8a-B Compétences transversales
    Variante B > BE1.7b-B Bereichsübergreifende Kompetenzen

    Educational Sciences 120
    Version: SA20_BA_de_v01
    BE1.8-D Bereichsübergreifende Kompetenzen

    Educational Sciences 120
    Version: SA14_BA_fr_v02
    CTC / BS1.8-F

    English Language and Literature 120
    Version: SA15_BA_ang_V02
    Module Nine: Soft Skills

    MiBa - Business Administration - 60 ECTS
    Version: 2015-SA_V01
    Au moins 31.5 ECTS de > Introduction à la statistique I / Einführung in die Statistik I

    MiBa - Business Communication : Economics - 60 ECTS
    Version: 2022_SA_V01
    Economics - 30 ECTS > Bachelor level elective course - 6 ECTS > Elective courses BA SES

    MiBa - Economics - 30 ECTS
    Version: 2009-SA_V01
    Cours facultatifs à choisir: Cours bachelor (sans cours de langue) de la Faculté des sciences économiques et sociales > Elective courses BA SES

    MiBa - Economie politique - 60 ECTS
    Version: 2009-SA_V01
    Cours facultatifs à choisir: Cours bachelor (sans cours de langue) de la Faculté des sciences économiques et sociales > Elective courses BA SES

    Psychology 180
    Version: SA19_BA_fr_de_bil_v02
    Module 11 > M11 Soft skills

    Slavic Studies 120
    Version: SA15_BA_slav_V01
    Module 9: Compétences transversales et complémentaires

    Slavic Studies 120
    Version: SA15_BA_slav_V02
    Module 9: Compétences transversales et complémentaires