Several lists/collections of links to resources related to research/teaching/career. See Readme for more details.
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Several lists/collections of links to resources related to research and teaching and career.

Lists are maintained by Andreas Handel.

If you have suggestions for updates/improvements or something doesn't work, let me know (using github issues or pull requests).

The majority of content in those lists are collections of links to other sources. Some contain a few of my own thoughts on specific topics. The content is heavily biased by my own work. For research topics, the focus is in statistics/data analysis, infectious disease modeling and the R programming language. The other lists focus on research/academic careers and topics related to it.

Some lists contain a decent amount of information, others are fairly short/empty. All of the lists are subject to (infrequent) change/updates - whenever I get to it or come across sources I find interesting enough to 'bookmark' by adding them to one of the lists.

The lists are written as Markdown files. You can just click on the .md files and github will render it looking (somewhat) nice and definitely readable.

Currently available lists are (in alphabetical order):

  • Information on (academic/research) career related resources.

  • Information on how to communicate (scientific) information to various audiences.

  • Information where to find available data online.

  • Information to help with data analysis and statistics related task, with a focus on R.

  • Information regarding exploratory data analysis and graphics/visualization (mainy in R).

  • Information that's useful for Infectious Disease modeling.

  • Information on how to learn about a new topic, stay up to date and manage literature references

  • Information on how to publish in the peer reviewed literature

  • Resources for learning R in general and with learning specific R topics.

  • Resources for writing R packages

  • Information covering the general idea of reproducible research (with a focus on the data analysis aspect) and links to tools (RMarkdown).

  • Information about basic stats topics, with a focus on conceptual (e.g. why p-values are mostly stupid, and similar ideas).

  • Information on efficient workflows for research, with a focus on data analysis, modeling, reproducibility and R

  • A list of commands for doing data cleaning/wrangling tasks that I often encounter (and keep forgetting how to do).

  • A list of commands for plotting in R (both base plot and ggplot) that I often encounter (and keep forgetting how to do).