The R package i2ds supports the course Introduction to Data Science (using R, ADILT) at the University of Konstanz.
The i2ds package provides datasets and functions used in the examples and exercises of the book Introduction to Data Science (by Hansjoerg Neth, University of Konstanz, 2023), available at https://bookdown.org/hneth/i2ds/. The book and course provide a gentle introduction into the principles and methods of data science to students of psychology and other natural or social sciences. The R package i2ds primarily provides datasets, but also functions for data generation and manipulation that are used in the book’s examples and exercises. All functions included in i2ds are designed to be explicit and instructive, rather than efficient or elegant.
The textbook Introduction to Data Science is available at https://bookdown.org/hneth/i2ds/.
This course provides a gentle introduction to data science for students of any discipline with little or no background in data analysis or computer programming. Based on notions of representation, measurement, and modeling, we examine key data types (e.g., logicals, numbers, text) and learn to clean, summarize, transform, and visualize (rectangular) data. By reflecting on the relations between representations, tasks, and tools, the course promotes data literacy and cultivates reproducible research practices that precede and enable practical uses of programming or statistics.
The course uses the technologies provided by R (R Core Team, 2020), RStudio, RMarkdown, including key packages of the tidyverse (Wickham et al., 2019) (e.g., dplyr, ggplot2, tibble, and tidyr).
- Introduction to data science: Basics (using R, ADILT) (PSY-16620) at the University of Konstanz by Hansjörg Neth (h.neth@uni.kn, SPDS, office D507).
- Autumn/Winter 2023: Mondays, 13:30–15:00, D435.
- Course materials:
- Online platforms (at uni.kn):
The syllabus for the course Introduction to Data Science (using R, ADILT) at the University of Konstanz in Spring/Summer 2023 is currently under development.
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An initial syllabus for Introduction to Data Science is available at https://bookdown.org/hneth/i2ds/.
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The organizational details for this course are available on the ZEuS and Ilias web platforms.
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The textbook Data Science for Psychologists is available at https://bookdown.org/hneth/ds4psy/.
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Information on the Advanced Data and Information Literacy Track (ADILT) (en).
The main sript for this course is yet to be written. A textbook fragment Introduction to Data Science is:
- Neth, H. (forthcoming). i2ds: Introduction to Data Science.
Social Psychology and Decision Sciences, University of Konstanz, Germany.
Textbook (version 0.0.1, planned for 2023).
Available at https://bookdown.org/hneth/i2ds/.
In the meantime, we will be using several chapters from the textbook (2023):
- Neth, H. (2023). ds4psy: Data Science for Psychologists.
Social Psychology and Decision Sciences, University of Konstanz, Germany.
Textbook and R package (version 1.0.0, September 15, 2023). Available at https://bookdown.org/hneth/ds4psy/.
The URL of the supporting R package ds4psy (2023) is https://CRAN.R-project.org/package=ds4psy.
Chapters from the following textbooks (Baumer, Kaplan, & Horton, 2020; James, Witten, Hastie, & Tibshirani, 2021) are used for individual topics:
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Baumer, B. S., Kaplan, D. T., & Horton, N. J. (2021). Modern Data Science with R (2nd ed.).
CRC Press, Taylor & Francis Group, Boca Raton/London/New York.
Available at https://mdsr-book.github.io/mdsr2e/. -
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning (2nd edition). Springer, New York, NY.
Available at https://www.statlearning.com.
Additional details or readings may be announced if they are needed for individual sessions.
Introduction to Data Science (i2ds) by Hansjörg Neth is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Please ask any question that may also be of interest to other course members in the Discussion Forum on Ilias.
For all other questions, contact Hansjörg Neth (h dot neth at uni dot kn).
[File README.md updated 2023-09-20 by hn.]
Baumer, B. S., Kaplan, D. T., & Horton, N. J. (2020). Modern Data Science with R (2nd ed.). Retrieved from https://beanumber.github.io/mdsr2e/
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning with applications in R (2nd edition). Retrieved from https://www.statlearning.com/
Neth, Hansjörg. (2023). Data science for psychologists. Retrieved from https://bookdown.org/hneth/ds4psy/
Neth, H. (2023). ds4psy: Data science for psychologists. Retrieved from https://CRAN.R-project.org/package=ds4psy
R Core Team. (2020). R: A language and environment for statistical computing. Retrieved from https://www.R-project.org
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686