This collection of R tutorials accompanies the new course Data Analytics organized jointly in the bachelor curriculum “Wirtschaftswissenschaften” and the complementary subject area “Digital Science” at Universität Innsbruck and its Digital Science Center (DiSC).


Multivariate analysis and cluster analysis

  • Exploratory analysis (univariate, bivariate, multivariate)
  • Principal component analysis (PCA)
  • Cluster analysis (hierarchical, \(k\)-means)

Independence tests

  • Classical inference: \(t\)-test, \(F\)-test/ANOVA, \(\chi^2\)-test.
  • Nonparametric inference: Permutation tests, Wilcoxon-Mann-Whitney test.

Linear models

  • Multiple linear regression
  • AN(C)OVA
  • Model selection

Generalized linear models (GLMs)

  • Binary response variables (logit, probit)
  • Count data (Poisson)


In addition to this collection of R tutorials, further resources are available in the OLAT course at https://lms.uibk.ac.at/url/RepositoryEntry/4487970842, including the PDF slides, data sets, and some R scripts.


To make all output in the tutorial somewhat easier to read and digest, only four significant digits are employed instead of the “factory-fresh” seven:

options(digits = 4)