Overview

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).

Topics

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)

Resources

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.

Style

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)