Course
Intro to R for Bio and Enviro Sciences
ENVS 396, 3 Credits, Fall 2023
Instructor
Dr. Justin Pomeranz (he/him)
Office: 230E Wubben Science
Email: jpomeranz@coloradomesa.edu
Class Location
Wubben Science (WS) 245
Class Meeting Times
MWF, 3:00-3:50 pm MT
Office Hours
Times:
MWF, 11:00-11:50 am MT
Tuesday, Zoom by appointment
Location: 230E Wubben Science
Or by appointment. Note: my schedule gets very busy during the semester so please try to schedule appointments as far in advance as possible. In general it will be very difficult to set up appointments less than 24 hours in advance.
Website
The syllabus and other relevant class information and resources will be posted at https://jpomz.github.io/ENVS396-FA-2023/. Changes to the schedule will be posted to this site so please try to check it periodically for updates.
Course Communications
Email: jpomeranz@coloradomesa.edu This is the best way to get in touch with me. Please include the course code [ENVS396] and a brief description of the topic in the email subject line.
D2L: Course announcements and class-wide emails will be delivered via D2L. Please check it regularly.
Required Texts
There is no required text book for this class.
All needed material is openly available on the course website. If you are interested in additional reading on the topics we are covering I highly recommend R for Data Science, which is freely available on the web.
Course Description
An introduction to data management, manipulation, and analysis, with an emphasis on environmental and biological problems. Class consists of short introductions to new concepts followed by hands on computing exercises using R, but the concepts apply to programming languages and databases more generally. No background in computing is required.
Prerequisite Knowledge and Skills
Knowledge of basic environmental science and biology to provide context for exercises.
Purpose of Course
In this course you will learn all of the fundamental aspects of computer programming that are necessary for conducting research in the environmental and biological sciences. By the end of the course you will be able to use these tools to import data into R, perform analysis on that data, and export the results to graphs, text files, and .csv (comma separated value) files. By learning how to get the computer to do your work for you, you will be able to do more science faster.
Course Objectives and Goals
Students completing this course will be able to:
- Create well structured data
- Extract information from data
- Write computer programs in R
- Automate data analysis
- Apply these tools to address environmental and biological questions
- Apply general data management and analysis concepts to other programming languages and database management systems
How this course relates to the Student Learning Outcomes in Environmental Science
This course contributes to the ‘Quantitative Skills’ Student Learning Outcomes specified in the Environmental Science and Technology (BS) page, by providing students the skills and knowledge they need to manage and analyze the data used in research.
Teaching Philosophy
This class is taught using a flipped, learner-centered, approach, because learning to program and work with data requires actively working on computers. Flipped classes work well for all kinds of content, but I think they work particularly well for computer oriented classes. If you’re interested in knowing more take a look at this great flipped classroom info-graphic.
Instructional Methods
As a flipped classroom, students are provided with either reading or video material that they are expected to view/read prior to class. Classes will involve brief refreshers on new concepts followed by working on exercises in class that cover that concept. While students are working on exercises the instructor will actively engage with students to help them understand material they find confusing, explain misunderstandings and help identify mistakes that are preventing students from completing the exercises, and discuss novel applications and alternative approaches to the data analysis challenges students are attempting to solve. For more challenging topics class may start with 20-30 minute demonstrations on the concepts followed by time to work on exercises.
Course Policies
Attendance Policy
Attendance will not be taken or factor into the grades for this class. However, experience suggests that students who regularly miss class often struggle to learn the material.
Quiz/Exam Policy
There are no quizzes or exams in this course.
Make-up policy
Life happens and therefore there is an automatic grace period of 48 hours for the submission of late assignments with no need to request an extension. However, it is highly recommended that you submit assignments on time when possible because assignments build on one another and it can be hard to catch up if you fall behind. Reasonable requests for longer extensions will also be granted. Assignments turned in after the 48 hour grace period without an extension will be be graded with a 50% penalty.
Assignment policy
Assignments are due Sunday night by 11:59 pm Mountain Time. This timing allows you to be finished with one week’s material before starting the next week’s material. Assignments should be submitted via the course D2L webpage.
Course Technology
Students are required to provide their own laptops and to install free and open source software on those laptops (see Setup for installation instructions). Support will be provided by the instructor in the installation of required software. If you don’t have access to a laptop please contact the instructor and they will do their best to provide you with a departmental machine.
Materials and Supplies Fees
There are no materials and supplies fees for this course.
CMU Policies
Students should be aware of all official CMU policies as well as the Student Code of Conduct as described in the The Maverick Guide
My policy: If you are in my class I want to help you learn and will happily work with you to make the learning environment equitable for you and others.
Academic Honesty and Integrity
The faculty, administration, and students of Colorado Mesa University support the principle that all individuals associated with the academic community have a responsibility for establishing, maintaining, and fostering an understanding and appreciation for academic integrity.
Academic dishonesty undermines the educational experience, lowers morale by engendering a skeptical attitude about the quality of education, and negatively affects the relationship between students and faculty. Academic dishonesty is the intentional act of fraud in an academic environment/situation/exercise
Academic dishonesty includes, but is not limited to:
- Forgery/fabrication/falsification/plagiarism of academic documents
- Intentionally impeding or damaging the academic work of others
- Assisting others in acts of academic dishonesty
- Cheating in the classroom
- Unauthorized attendance
- Multiple submissions of the same material to two or more different classes without the permission of all instructors involved
- Unauthorized collaboration
- Lying/misrepresentation/omission of information to obtain an unfair advantage in an academic environment/situation/exercise
- Unauthorized use of materials or equipment to complete an academic requirement
- Any academic misconduct may be reported to the Department Head and Office of Academic Affairs and may result in a failing grade, suspension, or dismissal.
These policies are outlined in The Maverick Guide
Netiquette and Communication Courtesy
All members of the class are expected to follow rules of common courtesy in all email messages, threaded discussions and chats.
Software Use
All faculty, staff and students of the university are required and expected to obey the laws and legal agreements governing software use. Failure to do so can lead to monetary damages and/or criminal penalties for the individual violator. Because such violations are also against university policies and rules, disciplinary action will be taken as appropriate.
Grading Policies
Grading for this course is based on 15 equally weighted homework assignments.
Exercises in assignments will be graded as follows:
- Produces the correct answer using the requested approach: 100%
- Generally uses the right approach, but a minor mistake results in an incorrect answer: 90%
- Attempts to solve the problem and makes some progress using the core concept: 50%
- Answer demonstrates a lack of understanding of the core concept: 0%
Grading scale
- A 89.5-100
- B 79.5-89.4
- C 69.5-79.4
- D 59.5-69.4
- F <60
Student Services
As a student at CMU, you are entitled to services and have access to numerous resources. A full description can be found at the student services web page
It’s Ok to Not Be OK
Everyone struggles with their mental health at times, and college students are no exception. In fact, mental health struggles can impact your academic performance, and is associated with higher rates of drop out. Don’t let being stressed, depressed, anxious, or struggles with alcohol and drugs hinder your success at CMU. Please reach out for help if you need it!
CMU offers affordable counseling sessions at the CMU Student Wellness Center. Call 970-644-3740, ext #4 to set up an appointment or connect with Student Services at 970-248-1633 for resources on how to get help. Further, when people become overwhelmed with life, they can begin to have thoughts of suicide or self-harm. If you find yourself in this place, you can also call the National Suicide Prevention Lifeline at 800-273-8255. It is just as important that we look out for other Mavs if we see them struggling with their mental health. You may report your concerns about a friend or anyone else on campus using the Report It function.
Academic Resources
A full list of academic resources, including the Tutorial Learning Center (TLC), the Writing center, library resources, and IT help can be found in the Academic Services page
Course Schedule
The details course schedule is available on the course website at: https://jpomz.github.io/ENVS396-FA-2023//schedule.