Syllabus

Course Description

This course is meant to be a gentle introduction to data wrangling and visualization using the tidyverse in R. This course focuses on practical data science skills in R (loading data, data wrangling, visualization, automation, machine learning, and running statistical models) that you’ll use almost everyday in your work. It is meant for both beginners and students wanting to brush up on their R skills.

Credit Hours

3 credit hours.

Learning Objectives

1. Understand and utilize R/RStudio.
2. Understand basic data types and data structures in R.
3. Familiarize and load data files (Excel, Comma Separated Value files) into R/Rstudio, with tips on formatting.
4. Visualize datasets using ggplot2 and understand how to build basic plots using ggplot2 syntax.
5. Filter and format data in R for use with various routines.
6. Execute and Interpret some basic statistics in R.
7. Automate repetitive tasks in R, such as loading a folder of files.

If time allows:

8. Create nice tables in our R markdown reports with gt and/or kableExtra.
9. Build basic interactive applications with shiny.

Course Website

All course information will be available here:

https://sph-r-programming-2023.netlify.com/

Information will also be available on the Sakai website.

Course discussions will be done in the class Slack channel. Invites will be sent before class.

Office Hours

Office Hours will be held by request via Zoom using the class zoom link (see Sakai, or, outlook invite). Use the office hours request form (see Sakai for link) to request a 30 minute individual or small group meeting with me.

Prerequisites or Concurrent Enrollment Requirements

One course in statistics.

Faculty Information

Attendance Requirements

Please try to attend class, but I understand that sometimes it’s easier or necessary to log in virtually or watch a recording. Attendance is part of the grade but I only require that you fill out 5 post-class surveys (out of 11) as a way of telling me that you watched the recordings or came to class and learned the available material for that week. However, if you fill out all 11 surveys, your attendance score will be 11/5 so you have some easy extra credit available there as well.

Classes will be recorded, but I cannot guarantee the in person format will lend itself to effective recordings. Again, those who are curious and ask questions will learn quite a bit. You can go through all of last year’s materials on your own, but you signed up for a live in person course so definitely make the most of having people around to answer your questions!

Homework

There will be homework assigned weekly using R markdown. It will be due via Sakai upload at 11:55pm the night of the following week’s class (unless otherwise noted). Please turn in both your .Rmd and knitted .html file.

The homework with the lowest score will be dropped from the calculation. Some homeworks may have extra credit, so it’s possible to obtain > 100% on the homework portion.

Function of the week

Please choose a function from the function of the week sign up sheet (see Sakai homepage for link). In the dropbox folder there is a template for format of the week R markdown and presentation. You may choose a week to present your function to the class. The presentation should be short, around 5 minutes. If presenting to the class feels prohibitive, you may submit a 5-10 minute screen recording with your voice narrating the presentation, and this will be distributed to the class. Function of the week presentations will start in week 4.

Midterm and Final

Midterm and final projects/tests will be take home. The midterm will be a project based on a data set. The final will likely be based on a data set that I assign. Previous years’ midterms can be found on the class websites:

• https://sph-r-programming-2022-midterms.netlify.app/
• https://sph-midterm-projects.netlify.app/ (2021)

I will create a similar website for this year’s midterm projects. If you do not wish your project to be on the public facing website, just let me know. Or, it can be posted anonymously.

Grading Policy

• Attendance 5%
• Midterm Project 20%
• Function of the Week 10%
• Homework Assignments 45%
• Final Project 20%

Code of Conduct

This class is governed by the BioData Club Code of Conduct: https://biodata-club.github.io/code_of_conduct/

And as students of an OHSU course, we must abide by the OHSU Code of Conduct: https://www.ohsu.edu/integrity-department/code-conduct

This class is meant to be a psychologically safe space where it’s ok to ask questions. We want to normalize your own curiosity and fuel your desire to learn more.

If you are disruptive to class learning or disparaging to other students, I may mute you for the day. I am very serious about this.

Required Texts or Readings

We will be drawing on the following online textbooks during class and labs. These books are online and free, though you can order them as textbooks if you prefer that format.

R for Data Science. Garret Grolemund and Hadley Wickham. https://r4ds.had.co.nz/

Getting Used to R, RStudio, and RMarkdown. Chester Ismay. https://ismayc.github.io/rbasics-book/

Data Science: A First Introduction. Tiffany Timbers, Trevor Campbell, Melissa Lee. https://datasciencebook.ca/

RMarkdown for Scientists. Nick Tierney. https://rmd4sci.njtierney.com/

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse. Chester Ismay and Albert Y. Kim. https://moderndive.com/

Advanced R. Hadley Wickham. https://adv-r.hadley.nz/

Words of Encouragement

This was adopted from Andrew Heiss. Thanks!

I promise you can succeed in this class.

Learning R can be difficult at first—it’s like learning a new language, just like Spanish, French, or Chinese. Hadley Wickham—the chief data scientist at RStudio and the author of some amazing R packages you’ll be using like ggplot2—made this wise observation:

It’s easy when you start out programming to get really frustrated and think, “Oh it’s me, I’m really stupid,” or, “I’m not made out to program.” But, that is absolutely not the case. Everyone gets frustrated. I still get frustrated occasionally when writing R code. It’s just a natural part of programming. So, it happens to everyone and gets less and less over time. Don’t blame yourself. Just take a break, do something fun, and then come back and try again later.

Even experienced programmers find themselves bashing their heads against seemingly intractable errors. If you’re finding yourself taking way too long hitting your head against a wall and not understanding, take a break, talk to classmates, e-mail me, etc.

LeaRning is Social

The students who have a bad time in my workshops and courses are the ones who don’t work with each other to learn. We are a learning community, and we should help each other to learn.

If you understand something and someone is struggling with it, try and help them. If you are struggling, take a breath, and try to pinpoint what you are struggling with.

Our goal is to be better programmers each day, not to be the perfect programmer. There’s no such thing as a perfect programmer. I’ve been learning new things almost every day.

Copyright Information

Every reasonable effort has been made to protect the copyright requirements of materials used in this course. Class participants are warned not to copy, audio, or videotape in violation of copyright laws.

Journal articles will be kept on reserve at the library or online for student access. Copyright law does allow for making one personal copy of each article from the original article. This limit also applies to electronic sources.

To comply with the fair use fair use doctrine of the US copyright law, Sakai course sites close three weeks after grades are posted with the Registrar. Please be sure to download all course material you wish to keep before this time as you will have no further access to your courses.

School of Public Health Handbook

All students are responsible for following the policies and expectations outlined in the student handbook for their program of study. Students are responsible for their own academic work and are expected to have read and practice principles of academic honesty, as presented in the handbook: https://ohsu-psu-sph.org/graduate-students-policies-and-procedures-2/

Syllabus Changes and Retention

This syllabus is not to be considered a contract between the student and the School of Public Health. It is recognized that changes may be made as the need arises. Students are responsible for keeping a copy of the course syllabus for their records.

Syllabi are considered to be a learning agreement between students and the faculty of record. Information contained in syllabi, other than the minimum requirements, may be subject to change as deemed appropriate by the faculty of record in concurrence with the academic program and the Office of the Provost. Refer to the Course Syllabi Policy, 02-50-050.

Syllabus Statement Regarding Disability Services

OHSU is committed to providing equal access to qualified students who experience a disability in compliance with Section 504 of the Rehabilitation Act of 1973, the Americans with Disabilities Act (ADA) of 1990, and the ADA Amendments Act (ADA-AA) of 2008. If you have a disability or think you may have a disability (physical, sensory, chronic health, psychological or learning) please contact the Office for Student Access at (503) 494-0082 or studentaccess@ohsu.edu to discuss eligibility for academic accommodations. Information is also available at www.ohsu.edu/student-access. Because accommodations may take time to implement and cannot be applied retroactively, it is important to have this discussion as soon as possible. All information regarding a student’s disability is kept in accordance with relevant state and federal laws.

Please see Student Access & Accomodations section for more details on the Sakai version of this Syllabus.

Commitment of Equity and Inclusion

The School of Public Health is committed to providing an environment free of all forms of prohibited discrimination and discriminatory harassment. The School of Public Health students who have questions about an incident related to Title IX are welcome to contact either the OHSU or PSU’s Title IX Coordinator and they will direct you to the appropriate resource or office. Title IX pertains to any form of sex/gender discrimination, discriminatory harassment, sexual harassment or sexual violence.

PSU’s Title IX Coordinator is Julie Caron, she may be reached at titleixccordinator@pdx.edu or 503-725-4410. Julie’s office is located at 1600 SW 4th Ave, In the Richard and Maureen Neuberger Center RMNC - Suite 830.

The OHSU Title IX Coordinator’s may be reached at 503-494-0258 or titleix@ohsu.edu and is located at 2525 SW 3rd St.

Please note that faculty and the Title IX Coordinators will keep the information you disclose private but are not confidential. If you would like to speak with a confidential advocate, who will not disclose the information to a university official without your written consent, you may contact an advocate at PSU or OHSU.

PSU’s confidential advocates are available in Women’s Resource Center (serving all genders) in Smith Student Memorial Union 479. You may schedule an appointment by (503-725-5672) or schedule on line at https://psuwrc.youcanbook.me. For more information about resources at PSU, please see PSU’s Response to Sexual Misconduct website.

OHSU’s advocates are available through the Confidential Advocacy Program (CAP) at 833-495-CAPS (2277) or by email CAPsupport@ohsu.edu, but please note, email is not a secure form of communication. Also visit www.ohsu.edu/CAP.

At OHSU, if you encounter any harassment, or discrimination based on race, color, religion, age, national origin or ancestry, veteran or military status, sex, marital status, pregnancy or parenting status, sexual orientation, gender identity or expression, disability or any other protected status, please contact the Affirmative Action and Equal Opportunity (AAEO) Department at 503- 494-5148 or aaeo@ohsu.edu.

At PSU, you may contact the Office of Equity and Compliance if you experience any form of discrimination or discriminatory harassment as listed above at equityandcompliance@pdx.edu or by calling 503-725-5919.

Academic Honesty

Course participants are expected to maintain academic honesty in their course work. Participants should refrain from seeking past published solutions to any assignments. Literature and resources (including Internet resources) employed in fulfilling assignments must be cited. See http://www.ohsu.edu/xd/education/library/research-assistance/plagiarism.cfm?WT_rank=1# for information on code of conduct for OHSU and

http://www.ohsu.edu/xd/education/teaching-and-learning-center/for-students/index.cfm for more information on citing sources and recognizing plagiarism.

In an effort to uphold the principles and practice of academic honesty, faculty members at OHSU may use originality checking systems such as Turnitin to compare a student’s submitted work against multiple sources.

To protect student privacy in this process, it will be necessary to remove all personal information, i.e. student name, email address, student u-number, or any other personal information, from documents BEFORE submission.

Use of Sakai

This course will have an online component, which can be accessed through Sakai, OHSU’s online course management system. For any technical questions or if you need help logging in, please contact the Sakai Help Desk.

Hours: Sakai Help Desk is available Mon – Fri, 8 am – 9 pm and weekends 12 pm – 5 pm, Pacific Time.

Contact Information:

(Toll-free) 877-972-5249

(Web) http://atech.ohsu.edu/help

(Email) sakai@ohsu.edu