Chapter 22 Concluding remarks, next steps, and open problems
Last updated: 6 June 2021.
22.1 Concluding remarks
22.2 Next steps
This book has covered a lot of ground. Chances are there are aspects that you want to explore further, building on the foundation that you have established. If so, then I’ve accomplished what I set out to do.
For learning more about R in terms of data science, there is only one recommendation that is possible and that is Wickham and Grolemund (2017). To deepen your understanding of R itself, go next to Wickham (2019a).
There is only one next natural step if you’re interested in learning more about statistical (what’s come to be called machine) learning and that’s James et al. (2017) followed by Friedman, Tibshirani, and Hastie (2009).
If you’re interested in sampling then the next book to turn to is Lohr (2019). To deepen your understanding of surveys and experiments, go next to Gerber and Green (2012) in combination with Kohavi, Tang, and Xu (2020).
Graphs and communication in that regard should go to…
Writing go to…
Thinking through production and SQL and things like, a next natural step is…
22.3 Open problems
- Optimal names