Scientific Computing Resources

Scientific Computing Help Resources:

General:

  • Lynda.com is available through UCSB Instructional Development, to all faculty and staff, which includes grad students who TA/RA or something like that. Lynda.com has online instructional videos about all of the general computing topics we covered, including two short intros to R. They also have courses on most aspects of computer science, web development, photography, art, and design. You can sign into Lynda.com using this link: https://it.ucsb.edu/services/lynda then search or browse for a relevant course.

  • StackExchange http://stackexchange.com/sites is a massive Q&A site of sites, and StackOverflow is the programming site within: http://stackoverflow.com/. If you have a question, and its not in here, congratulations on doing something completely original! You can add a question, but be sure you check the sites rules for submitting questions, and please try to include your (possibly faulty) code and a piece of your dataset so someone responding can replicate your work. On StackExchanges, you can even learn all the clubs Hermione Granger joined at Hogwarts.

The Shell

  • If you are on linux or mac, checkout man for help on shell commands
  • Stack exchange is also a great resource for bash scripts

Git and Version Control

R basics

  • http://www.statmethods.net/ has a little bit of everything in R, including some basics stats, basic ggplot, and a lot of quick and easy data management.

  • For most things R, from basics to advanced statistics, the UCSB library has many e-books, including many in Springer's Use R! series. If you can find it on Amazon, the UCSB library probably has it as an e-book. You can download entire books which is amazing if you are a true dirtbag and not interested in having stacks of textbooks on your floor.

  • R markdown cheatsheet: https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf. R markdown is a markdown language that allows you to create simply formatted documents that seamlessly integrate text and R code and results.

R data management

R graphics and ggplot2

Data management with SQL