Study programme 2018-2019Français
Data Sciences I : visualisation and inference
Activité d'apprentissage à la Faculty of Science
CodeLecturer(s)Associate Lecturer(s)Subsitute Lecturer(s) et other(s)
S-BIOG-006
  • GROSJEAN Philippe
      Language
      of instruction      		Language
      of assessment      		 HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term
      FrançaisFrançais2550000Q1

      Content of Learning Activity

      Software R, RStudio, git & Markdown. Importation and transformation of datasets. Visualisation of uni-, bi-, and multivariate data. Descriptive statistics; Mean; Median; Standard deviation; Variance; Q-Q plot; Boxplot; Histogram; Statistical population; Sampling; Inference; Probabilities; Statistic distribution; Central limit theorem; Confidence interval; Hypothesis test; Parametric and non parametric tests; Binomial, Poisson, Chi-2, Normal, Student t and F distributions; Student t-test; One and two factors ANOVA; Wilkoxon-Mann-Withney test, Kruskal-Wallis test; Correlation; Pearson; Spearman.

      Required Learning Resources/Tools

      Not applicable

      Recommended Learning Resources/Tools

      Not applicable

      Other Recommended Reading

      Barnier, J., 2018. Introduction à R et au tidyverse (https://juba.github.io/tidyverse/index.html). Ismay, Ch. & Kim A.Y, 2018. Moderndive: An introduction to statistical and data science via R (http://moderndive.com). Wickham, H. & Grolemund, G, 2017. R for data science (http://r4ds.had.co.nz). Cornillon, P.A. Et al, 2008. Statistiques avec R. Presses Universitaires de Rennes. 257pp. Dagnelie, P., 2007. Statistique théorique et appliquée, Volumes I et II (2ème ed.). De Boeck & Larcier, Bruxelles. 511pp (vol. I) 734pp (vol. II).

      Mode of delivery

      • Face to face
      • Mixed

      Type of Teaching Activity/Activities

      • Cours magistraux
      • Conférences
      • Exercices dirigés
      • Utilisation de logiciels
      • Démonstrations

      Evaluations

      The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)

      (*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
      More information on Higher Education Structure (’Paysage’ Decree)
      Date de génération : 02/05/2019
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