Sampling, Data Management and Visualization
NRES 898, 1 Credits, Spring 2017
Dr. Drew Tyre
Office: Hardin Hall 416
Email (best way to contact me): email@example.com
Times & Location
Note: class is in different locations depending on the day of the week
Tuesdays, 2-5, Online
Times: by appointment
Location: Hardin Hall 416
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.
The syllabus and other relevant class information and resources will be posted at http://atyre2.github.io/data-management. Changes to the schedule will be posted to this site so please try to check it periodically for updates.
There is no required text book for this class.
Computers are increasingly essential to the study of all aspects of biology. Data management skills are needed for entering data without errors, storing it in a usable way, and extracting key aspects of the data for analysis. Basic programming is required for everything from accessing and managing data, to statistical analysis, to modeling. This course will provide an introduction to data management, manipulation, and analysis, with an emphasis on biological problems. Class will typically consist of short introductions or question & answer sessions, followed by hands on computing exercises. The course will be taught using R, but the concepts learned will easily apply to all programming languages.
Prerequisite Knowledge and Skills
Knowledge of basic biology.
Purpose of Course
In this course you will learn all of the fundamental aspects of computer programming that are necessary for conducting biological research. 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 databases. By learning how to get the computer to do your work for you, you will be able to do more science faster.
Course Goals and Objectives
Students completing this course will be able to:
- Create well structured data
- Write simple computer programs in R
- Automate data analysis
- Apply these tools to address biological questions
- Apply general data management and analysis concepts to other programming languages and database management systems
This class is taught in an online approach, because learning to program and work with data requires actively working on computers. Online classes work well for all kinds of content, but I think they work particularly well for computer oriented classes.
Students interact in this course both synchronously and asynchronously. Students are provided with either reading or video material that they are expected to view/read prior to synchronous online sessions. Synchronous sessions 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 and TA 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 sessions may start with 20-30 minute demonstrations on the concepts followed by time to work on exercises.
Attendance will not be taken or factor into the grades for this class. However, experience suggests that students who regularly miss class struggle to learn the material.
There are no quizzes or exams in this course.
Assignments are due Tuesday night of the following week by 11:59 pm Eastern Time. Assignments should be submitted via Canvas. Late assignments will be docked 10% up to one week late, and 20% up to the end of the class, except in cases of genuine emergencies that can be documented by the student or in cases where this has been discussed and approved in advance. This policy is based on the idea that in order to learn how to use computers well, students should be working with them at multiple times each week. Time has been allotted in class for working on assignments and students are expected to work on them outside of class. It is intended that you should have finished as much of the assignment as you can based on what we have covered in class by the following class period. Therefore, even if something unexpected happens at the last minute you should already be close to done with the assignment. This policy also allows rapid feedback to be provided to students by returning assignments quickly.
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. Interaction in online sessions is greatly facilitated by using a USB connected headset with a microphone. It does not need to be expensive. The built-in microphone and speakers on a laptop are not sufficient.
Students with Disabilities
Students with disabilities are encouraged to contact the instructor for a confidential discussion of their individual needs for academic accommodation. It is the policy of the University of Nebraska-Lincoln to provide flexible and individualized accommodation to students with documented disabilities that may affect their ability to fully participate in course activities or to meet course requirements. To receive accommodation services, students must be registered with the Services for Students with Disabilities (SSD) office, 132 Canfield Administration, 472-3787 voice or TTY.
Student Code of Conduct
Students are expected to adhere to guidelines concerning academic dishonesty outlined in Article III B.1 of University’s Student Code of Conduct. A first offense will result in a 10% penalty on the assignment. A second offense will result in a grade of zero for the assignment. A third offense will result in a grade of F for the course. Students are encouraged to contact the instructor for clarification of these guidelines if they have questions or concerns. The SNR policy on Academic Dishonesty and procedures for appeals are available here.
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.
For login problems only: contact the UNL Computer Help Center Phone: (402) 472-3970 or toll-free (866) 472-3970 E-mail: firstname.lastname@example.org
Any requests for make-ups due to technical issues with Canvas MUST be accompanied by the ticket number received from the help center when the problem was reported to them. The ticket number will document the time and date of the problem. You MUST e-mail your instructor within 24 hours of the technical difficulty if you wish to request a make-up.
Most importantly, if you are struggling for any reason please come talk to me and I will do my best to help.
There will be one equally weighted assignment per week. One problem from each assignment (selected at the instructors discretion after the assignments have been submitted) will receive a thorough code review and a detailed grade. Other problems 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%
- A 90-100
- B+ 87-89
- B 80-86
- C+ 77-79
- C 70-76
- D+ 67-69
- D 60-66
- F <60
The details course schedule is available on the course website at: http://atyre2.github.io/data-management/schedule.
Disclaimer: This syllabus represents my current plans and objectives. As we go through the semester, those plans may need to change to enhance the class learning opportunity. Such changes, communicated clearly, are not unusual and should be expected.