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# 11 Continued learning

## 11.1 Free online books:

### 11.1.1 Beginner

- R for Data Science: Excellent open and online resource for using R for data analysis and data science.
- Fundamentals of Data Visualization: Excellent online resource for using ggplot2 and R graphics. The book mostly focuses on concepts and theory of how to visualize, rather than the practicalities (i.e. no coding involved).
- ModernDive: Statistical Inference via Data Science: Great book on using statistics and data science methods in R.
- Happy Git and GitHub for the useR (
**highly recommended**): Specifically useful is the chapter on Daily Workflows using Git. - Data Visualization: A practical introduction: A book that goes into practical as well as conceptual detail on how and why to make certain graphs, given your data.
- Course material for a statistics class: Excellent course material for teaching statistics and R.
- ModernDive: Statistical Inference via Data Science: Great book on using statistics and data science methods in R

### 11.1.2 Intermediate and above

- Efficient R Programming: Excellent book on being efficient when writing R code.
- Advanced R: Detailed book on advanced features of R.
- R Packages: Learn how to create R Packages from the basics.
- R Programming for Data Science: Great overview of using R for Data Science, with more of a focus on the programming side of things

## 11.2 Quick references:

- RStudio cheatsheets: Multiple, high-quality cheatsheets you can print off to use as a handy reference.
- Tidyverse style guide: To learn about how to write well-styled code in R.
- Tidyverse design philosophy of writing code

## 11.3 Articles:

- Good enough practicies in scientific computing: An article listing and describing some practices to use when writing code.
- Best practices in scientific computing.
- Case study of reproducible methodds in Bioinformatics: [@Kim2018a].

## 11.4 General sites:

- Organizing R Source Code.
- Hands-on tutorial for learning Git, in a web-based terminal.
- Simpler, first-steps guide to using Git.
- RStudio tutorial on using R Markdown.
- Markdown syntax guide.
- Pandoc Markdown Manual (R Markdown uses Pandoc).
- Adding citations in R Markdown.
- Case studies and lessons for doing reproducibility

## 11.5 Interactive sites or resources for hands-on learning:

## 11.6 Videos:

- Video on using Git in RStudio.

## 11.7 Getting help:

- StackOverflow for tidyr.
- StackOverflow for dplyr.
- StackOverflow for ggplot2.
- Tip: Combine auto-completion with
`::`

to find new functions and documentation on the functions (e.g. try typing`base::`

and then hitting Tab to show a list of all functions found in base R).