Literature

Literature¶

The course is mainly based on the following literature:

[IMS]: Çetinkaya-Rundel, M. & Hardin, J. (2021). Introduction to Modern Statistics. OpenIntro.
[ISL]: James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning. New York: Springer.

Minor parts are based on this literature:

[HML]: Géron, A. (2019). Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O’Reilly Media.
[TMWR]: Kuhn, M., Silge, J. (2021). Tidy Modeling with R.
[AOS]: Spiegelhalter, D. (2019). The Art of Statistics: Learning from Data. Penguin UK.

Further resources:

VanderPlas, J. (2016). Python data science handbook: essential tools for working with data. O’Reilly Media, Inc.

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