Ecol 596W – Programming for Data Analysis in R
Spring semester 2016
R Course Information
STUDENT INSTRUCTOR: PhD Candidate Ty Taylor.
Office: BSW 224. Email: firstname.lastname@example.org. Office hours: by appointment.
FACULTY SPONSOR: Assoc. Professor Scott Saleska.
Office: 510 BSW. Email: email@example.com. Office hours: by appointment.
COURSE MEETING: 10:00 – 11:30 AM Fridays, BSW 302
COURSE UPDATES: Homework announcements and course updates are made by email to the class email list and made available on the class dropbox. The course timeline will be updated online at the course website.
COURSE PREREQUISITES: No prerequisites. Course open to graduate and advanced undergraduate students with permission.
TEXT: The course is based around custom tutorials available online here: http://www.saleskalab.org/teaching/tutorials/r-tutorials/. Other additional resources will be posted on the course web page.
SYLLABUS: See the outlines on the tutorials page and in the course timeline on the course webpage for a topical outline.
EXAMS: No exams.
HOMEWORK: Homework is an essential aspect of the course. Weekly homework assignments will be due Fridays by the end of the day, unless stated otherwise. These are announced and made available by email to the class email list and on the class dropbox. Completed homework assignments are to be submitted by each student to their personal homework submission dropbox folder, or by email to the instructor if preferred. Late homework submissions will not be accepted for grading, unless agreed ahead of time by the instructor.
FINAL PROJECT: Due May 6. The instructions for the final project are as follows.
- Analyze your own data in R: Make this project useful to you by working with your own data, or with an available dataset of interest.
- Neatly formatted R script: The final product should be an R script that performs the data manipulation and analysis. This should be impeccably formatted, with clear section and sub-section headings, clear commenting, and nicely spaced code. Irrelevant sections of “scratch” test code and personal notes should be eliminated. You should be able to read and understand this script 10 years from now.
- Conduct a complete analysis involving:
- Data prep: Data should be altered as little as possible outside of R; do the data cleaning, organizing, merging, etc., in the R script.
- For loop and/or apply() function and/or custom function: Use at least one of these advanced techniques somewhere in your analysis. But, they must be necessary, e.g., do not use a for loop when R has a vectorized function that does the same thing faster, and do not use a custom function unless it provides additional flexibility over a fixed script.
- Statistical test and/or graph: Produce at least one interesting and useful statistical test and/or figure. Graphs should have clear and informative titles and axes. Bonus points for making them pretty with ggplot2!
- Bonus for summary tables from analyses: See examples from the class and homework exercises for making useful tables from your analyses. This is not required, but they are very useful for you!
Points: There will be 11 homework assignments worth 10 points each. The final project will be worth 30 points.
Homework assignment grades: Full points will be awarded if answers to all problems show strong effort, even if they are not correct or complete. Otherwise, points will be assigned according to the proportion of problems attempted. Homework is due on the Friday following the assignment. Late homework assignments will not be accepted for grading unless discussed and agreed ahead of time by the instructor.
Final project grades: Full points will be awarded for final project R scripts following the guidelines for the final project in the course syllabus. The points breakdown will be for neat formatting (5), data prep (5), for loop and/or apply() function and/or custom function (10), statistical test and/or graph (10). The code in the final project script must be functional code that produces the desired outcomes.
Final grade: The course percentage grade will be calculated as follows:
P = sum of points earned from homework assignments and the final project (after replacing the lowest homework grade with 10 points).
T = the total number of earnable points, 140.
Final grade = P / T.
WITHDRAWALS: Students withdrawing from the course before March 6 will receive the grade of W if they are passing at the time. Students will be considered passing at the time of withdrawal if they have scored at least 50% on the work completed at that time. The University allows withdraws after March 6, but only with the Dean’s signature and for an extraordinary reason. Late withdraws will be dealt with on a case by case basis, and requests for late withdraw with a W without a valid reason may or may not be honored.
INCOMPLETES: The grade of I will be awarded if the student has met all of the following conditions:
1. completed all but a small portion of the required work;
2. scored at least 50% on the work completed;
3. has a valid reason for not completing the course on time;
4. agrees to make up the uncompleted requirements within a short period of time;
5. asks for the incomplete before course grades are due (48 hours after the Final Exam).
ATTENDANCE: Students are expected to attend every scheduled class and to be familiar with the University Class Attendance Policy as it appears in the General Catalog. Frequent unexplained non-attendance may result in a student being dropped from the class. Experience has shown that regular class attendance is necessary for success in this course. It is the student’s responsibility to keep informed of any announcements, syllabus adjustments or policy changes made during scheduled classes.
SOME IMPORTANT DATES: (undergraduate dates; graduate student dates)
* Last day to drop without appearing as dropped (grade of W) on transcript (using UAccess): For undergraduates, Wednesday, January 27, 2016. For graduate students, Tuesday, February 9, 2016.
* Last day to withdraw online using UAccess (instructor and dean’s signature is required after this): All students, Monday, March 29, 2016.
* Spring recess, March 12-20, 2016
* Last class meeting: Friday, April 29, 2016
* Final projects due: May 6, 2016
CLASSROOM CONDUCT: Students at The University of Arizona are expected to conform to the standards of conduct established in the Student Code of Conduct. Prohibited conduct includes:
1. All forms of student academic dishonesty, including cheating, fabrication, facilitating academic dishonesty, and plagiarism.
2. Interfering with University or University-sponsored activities, including but not limited to classroom related activities, studying, teaching, research, intellectual or creative endeavor,administration, service or the provision of communication, computing or emergency services.
3. Endangering, threatening, or causing physical harm to any member of the University community or to oneself or causing reasonable apprehension of such harm.
4. Engaging in harassment or unlawful discriminatory activities on the basis of age, ethnicity, gender, handicapping condition, national origin, race, religion, sexual orientation, or veteran status, or violating University rules governing harassment or discrimination.
Students found to be in violation of the Code are subject to disciplinary action. For more information about the Student Code of Conduct, including a complete list of prohibited conduct, see http://dos.web.arizona.edu/uapolicies/scc5308f.html.
ACADEMIC INTEGRITY: Students are responsible to be informed of University policies regarding the Code of Academic Integrity. Students found to be in violation of the Code are subject to sanctions that will be determined by the severity of the infraction. The Code of Academic Integrity will be enforced in all areas of the course, including tests and homework. For more information about the Code of Academic Integrity policies and procedures, including information about student rights and responsibilities, see http://dos.web.arizona.edu/uapolicies/ .
STUDENTS WHO REQUIRE REASONABLE ACCOMMODATIONS BASED ON DISABILITY: Students planning to use accommodations for this course should privately identify themselves to their instructor within the first few days of class. These students must also provide the instructor with a letter of identification from the Disability Resource Center. This letter should include information about any accommodations you will need for the class, including accommodations for test taking. Students are also invited to discuss specific issues with the course instructor during regular office hours or by appointment.