Statistics with R (Statistics)

  • Teaching

    Details

    Faculty Faculty of Humanities
    Domain Psychology
    Code UE-L25.01483
    Languages English
    Type of lesson Lecture
    Level Master
    Semester AS-2026

    Schedules and rooms

    Summary schedule Monday 08:15 - 10:00, Hebdomadaire (Autumn semester)

    Teaching

    Responsibles
    • Sokhn Nayla
    Teachers
    • Sokhn Nayla
    Description

    Interface and Vectors

    • Recap basic concepts like vectors, data types (numeric, character, logical), indexing, and basic operations (arithmetic, logical)
    • Data manipulation using vectors in R

    Importing Data and Writing Data

    • Importing different file formats (csv and text files) using read.csv, read.table
    • Exporting data (write.csv, write.table)

    Descriptive Stats

    • Compute descriptive statistics such as mean, median, mode, variance, standard deviation, skewness, kurtosis, etc

    Visualisazion of the data

    • Explore various types of plots: boxplots, scatter plots, histograms, bar plots, etc.
    • Use packages like ggplot2 for more advanced and customizable visualizations.

    Parametric and Non Parametric Tests

    • Pearson Correlation/Chi-square tests/T-tests/ANOVA (one-way, factorial)
    • Spearman Correlation/Wilcoxon signed-rank test/Mann-Whitney U test/Kruskal Wallis
    Softskills No
    Off field No
    BeNeFri No
    Mobility Yes
    UniPop No
  • Dates and rooms
    Date Hour Type of lesson Place
    21.09.2026 08:15 - 10:00 Cours
    28.09.2026 08:15 - 10:00 Cours
    05.10.2026 08:15 - 10:00 Cours
    12.10.2026 08:15 - 10:00 Cours
    19.10.2026 08:15 - 10:00 Cours
    26.10.2026 08:15 - 10:00 Cours
    02.11.2026 08:15 - 10:00 Cours
  • Assessments methods

    Exam - AS-2026, Session d'hiver 2027

    Assessments methods By rating

    Exam - SS-2027, Session d'été 2027

    Assessments methods By rating

    Exam - SS-2027, Autumn Session 2027

    Assessments methods By rating

    Exam - AS-2027, Session d'hiver 2028

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Clinical Neuroscience 30 [MA]
    Version: SA25_MA_PS_fr_de_bil_v01
    Fondements en neurosciences cognitives
    Cognitive Neuroscience 30 [MA]
    Version: SA25_MA_PS_en_v01
    Fondements en neurosciences cognitives
    Developmental Neuroscience 30 [MA]
    Version: SA25_MA_PS_fr_v01
    Fondements en neurosciences cognitives
    Psychology 30 [MA]
    Version: SA26_MA_P2_fr_de_bil_v01
    1 module à choix > Fondements en neurosciences cognitives
    Psychology 30 [MA]
    Version: SA18_MA_P2_fr_de_bil_v01
    Specialisation Module > Cognitive Neuroscience > Methods in Cognitive Neuroscience (NCS B)
    Psychology 30 [MA]
    Version: SA21_MA_PS_fr_de_bil_v01
    Option Work & Organisational Psychology > Méthodes en neurosciences cognitives
    Option Developmental & School Psychology > Méthodes en neurosciences cognitives
    Option Clinical Psychology & Health Psychology > 1 module à choix > Méthodes en neurosciences cognitives
    Option Clinical Neuroscience > Méthodes en neurosciences cognitives
    Psychology 30 [MA]
    Version: SA22_MA_PS_fr_de_bil_v01
    Option Work & Organisational Psychology > Méthodes en neurosciences cognitives
    Option Developmental & School Psychology > Méthodes en neurosciences cognitives
    Option Clinical Neuroscience > Méthodes en neurosciences cognitives
    Option Clinical Psychology & Health Psychology > 1 module à choix > Méthodes en neurosciences cognitives
    Psychology 90 [MA]
    Version: SA22_MA_PA_fr_de_bil_v01
    Options > Cognitive Neuroscience > Méthodes en neurosciences cognitives
    Psychology 90 [MA]
    Version: SA21_MA_PA_fr_de_bil_v01
    Options > Cognitive Neuroscience > Méthodes en neurosciences cognitives