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Introduction to Data Science

About

i2ds 1

This book is still being written and revised to teach the course Introduction to Data Science (using R, ADILT) at the University of Konstanz in 2025. It currently serves as a scaffold for the curriculum that will be filled with content as we go along.

Contents and audience

This book will eventually contain materials needed to teach a variety of introductory courses on data science for undergraduate students of various disciplines. The materials and examples are designed to engage and motivate students from different fields to apply computational tools to solve challenging problems. Hopefully, students from all backgrounds and levels of experience will welcome the summaries of essential commands and find solving the exercises both enjoyable and enlightening.

Potential courses

The materials covered in the parts and chapters of this book can flexibly arranged to support both basic and more advanced courses and curricula:

  • An introductory course would cover Parts 1 to 3, with selected chapters from Parts 4 and 5. Combining chapters of Parts 1,  2 and 3 could provide a basic introduction to data literacy and reproducible research that is using R for visualizing data, but would not be focusing on particular packages of the tidyverse.
  • Based on student needs and a course’s goals and scope, some of the more specialized chapters (e.g., in Parts 3 to 6) can first be skipped, but used as elements of more advanced curricula later. Potential courses could focus on data visualization (Part 3), on specific data types (Part 5), or on applications (Part 6).

Providing feedback

As this text is still being revised and data science is a dynamic field, it is likely that the current version contains some typos and mistakes. Please email me (as h.neth at uni.kn) to report any errors, possible improvements, or any other feedback or observations that you are willing to share.

Citing and linking

Everyone likes being linked or cited. Feel free to adopt this book or parts of it to your own purposes, but please acknowledge its use in your own work.

i2ds 2

  • Neth, H. (2025). i2ds: Introduction to Data Science.
    Social Psychology and Decision Sciences, University of Konstanz, Germany. Online textbook (version 0.5.9, September 18, 2025). Retrieved from https://bookdown.org/hneth/i2ds/.

Online links:

Data science for psychologists (ds4psy)

The book has been started as a more detailed and extensive version of Data Science for Psychologists (Neth, 2025a) and uses the corresponding R package ds4psy (Neth, 2025b). The full reference of this companion book and package:

ds4psy package

A BibTeX entry for LaTeX users is:

@Manual{,
  title = {ds4psy: Data Science for Psychologists},
  author = {Hansjörg Neth},
  year = {2025},
  organization = {Social Psychology and Decision Sciences, University of Konstanz},
  address = {Konstanz, Germany},
  note = {R package (version 1.1.0, September 12, 2025); Textbook at <https://bookdown.org/hneth/ds4psy/>.},
  url = {https://CRAN.R-project.org/package=ds4psy},
  doi = {10.5281/zenodo.7229812},
}

Online links:

License

Creative Commons License

Introduction to data science (i2ds) by Hansjörg Neth is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The HTML-version of this book uses Google Analytics to evaluate the popularity of its different chapters. The website does not collect any personal data of individual users.

Colophon

This book is still being written. Its current version was generated using R version 4.5.0 (2025-04-11) and the following packages:

  • base (4.5.0), bookdown (0.44), bslib (0.9.0), colorspace (2.1.1), datasets (4.5.0), dplyr (1.1.4), ds4psy (1.1.0.9002), FFTrees (2.1.0), forcats (1.0.0), ggplot2 (3.5.2), graphics (4.5.0), grDevices (4.5.0), here (1.0.1), HistData (0.9.3), knitr (1.50), lubridate (1.9.4), methods (4.5.0), palmerpenguins (0.1.1), purrr (1.1.0), RColorBrewer (1.1.3), readr (2.1.5), riskyr (0.5.0.9002), rmarkdown (2.29), shiny (1.11.1), shinythemes (1.2.0), shinyWidgets (0.9.0), stats (4.5.0), stringr (1.5.2), tibble (3.3.0), tidyr (1.3.1), tidyverse (2.0.0), unicol (0.4.0.9001), unikn (1.0.0.9004), utils (4.5.0).

Thanks to all package authors and the wonderful R community for making this book possible!