Syllabus

Zool691B R Bootcamp (1cr, 3 week intensive)

Instructor

Dr. Marguerite Butler, mbutler808_at_gmail_dot_com
Edmondson 316
Office Hours by appointment

Scope

This course is designed to introduce Life Science students to elements of the R statistical computing environment for scientific computing and data analysis. During an intense 3 week bootcamp, students will be introduced to:  (1) Basic programming principles and syntax, (2)  objects and how to manipulate them (3) introduction of data structures, and (4) demonstration of graphics and statistics. The aim is to develop practical data-science skills, self-confidence, and sufficient background so that students can continue learning in the R code universe. This course is ideal for students planning to enroll in biometry, statistics, or other courses using R.

Students will be writing code, learning how to debug and troubleshoot their own code, as well as learning how to interact with their computer systems. We will discuss best practices for data analysis. The course will be presented in lectures and demonstrations. Students are expected to attend class, do tutorial-type exercises at home, review examples, and complete all homework assignments. Similar to learning a foreign language, programming is only learned by doing and trying things out. Undersanding Japanese  as well as continually refining your code. Just as you learn writing by revising your work when you learn better techniques, you learn how to program by revising as your skills evolve. The more you do, the more you will learn. 

Course Assignments

Homework  50%

Homeworks should be turned posting it in on GitHub classroom. Homework grades will be averaged.

Quizzes  25%

Participation/Effort  25%

Students can earn participation credit by completing and annotating readings, participate in discussion and in-class activities, responding to Slack conversations, and by any other means. Every student is expected to fully participate, and effort matters a lot.

Course Schedule

Classes start January 11
BOOTCAMP: 8-9:20am M, W, F, Jan 11-Jan 29. No class on MLK day.

  1. R environment
  2. Objects – data types
  3. Git – R workflow, Manipulating Objects, Scripts
  4. Indexing using logical vectors
  5. Data Input/Output, Writing Functions, Putting it together
  6. Loops and scaling up
  7. Data Cleaning – Spring Matching, Manipulation, Replacement
  8. Some fun stuff in R

Course Materials

Students are responsible for checking the course website http://Rbootcamp.butlerlab.org for all materials and changes to the schedule.

Reading assignments will be posted on Laulima, and annotations should be made through Perusall on the “Lessons” tab.

Homework assignments, and repositories for code, data, and R histories will be posted on GitHub repositories, accessed via Git. https://github.com/Rbootcamp-UHM

Preferred communication is via course Slack channel. Email is OK too.