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In this first part, we present some fundamental material of statistics and data analysis, and R-specific issues that we regularly encounter during data analyses. This is also a commented collection of R-code that we documented for our own work. We hope this might be useful also for other readers.
## Further reading
- [An Introduction to R](https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf) is an introduction and manual for basic R usage.
- [R for Data Science](https://r4ds.hadley.nz/spreadsheets): Introduces the tidyverse framework, explains how to get data into R, get it into the most useful structure, transform it, visualise it and model it.