Introduction to Data Analysis for Aquatic Sciences

A newish course with a focus on R - no experience required

Creative Commons License

Course Dev Info

Syllabus

Introduction to Data Analysis for Aquatic Sciences

FISH 274, 3 Credits, Autumn 2019

Professor

Dr. Steven Roberts

Office: FTR 232

Email: sr320@uw.edu

Phone: 206-866-5141

Times & Location

Tuesdays, 9:30 – 11:20AM, FSH 213

Thursdays, 9:30 – 10:50AM, FSH 213

Website

The syllabus and other relevant class information and resources will be posted at https://sr320.github.io/course-fish274-2019. Changes to the schedule will be posted to this site so please try to check it periodically for updates.

Reading Materials

All required reading material can found on the course website in the schedule. Most readings will be in R for Data Science by Garrett Grolemund and Hadley Wickham. A version of the textbook is available free online at http://r4ds.had.co.nz/. Additional readings will include material developed as part of the Data Carpentry: Ecology Curriculum and R vignettes. Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research.

Course Description

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. 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 bash, R, and Jupyter Notebooks, but the concepts learned will easily apply to all other computational work. There will be an emphasis on reproducible research which includes the use of R markdown and version control. Students will need to come to class each week having completed the assigned readings. Once we learn how to import data, we will explore basic analysis procedures involving summarizing, gathering, spreading, filtering, separating, uniting, selecting, counting, random sampling, and performing basic arithmetic. The course will culminate in students identifying a data set, identifying a specific research question that can be answered with the data set, and communicate the findings in an effective visual manner. Work on these student projects will begin during week 6 of the course and students will present their work to the class during week 10.

Prerequisite Knowledge and Skills

Knowledge of basic biology.

Course Objectives

In this course you will learn fundamental aspects of data acquisition, data wrangling, and visualization that are necessary for conducting biological and ecological research. By the end of the course you will be able to import data into R, perform analysis on that data, and export the results to graphs, and presentations. Upon learning basic skills, students will identify a research question and corresponding data set to analyze. By learning how to get the computer to do your work for you, you will be able to more effectively analyze complex data sets and communicate the findings of your analyses.

Learning Goals

Students completing this course will be able to:

Teaching Philosophy

This class is taught using a partially 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.

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 struggle to learn the material.

Make-up policy

Late assignments will be docked 50% and will not be accepted more than 24 hours late 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.

Assignment policy

Assignments are due Friday night by 11:59 pm Pacific Time. Assignments should be submitted via Canvas.

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. The Student Technology Loan Program (https://stlp.uw.edu/) also allows students to borrow laptops on a first come, first serve basis.

UW Policies

University Policy on Accommodating Students with Disabilities

It is crucial that all students in this class have access to the full range of learning experiences. At the University of Washington, it is the policy and practice to create inclusive and accessible learning environments consistent with federal and state law. Full participation in this course requires the following types of engagement: Working with computers in the classroom and outside of the classroom, working in small groups. If you anticipate or experience barriers to your learning or full participation in this course based on a physical, learning, or mental health disability, please immediately contact the instructor to discuss possible accommodations. A more complete description of the disability policy of the College of the Environment can be found here. If you have, or think you have, a temporary or permanent disability that impacts your participation in any course, please also contact Disability Resources for Students (DRS) at: 206–543–8924 V / 206–543–8925 TDD / uwdss@uw.edu / http://www.uw.edu/students/drs.

University Policy on Academic Misconduct

Passing anyone else’s scholarly work (which can include written material, exam answers, graphics or other images, and even ideas) as your own, without proper attribution, is considered academic misconduct. Anyone engaging in academic misconduct will not receive credit for the course

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.

Getting Help

Most importantly, if you are struggling for any reason please come talk to me and I will do my best to help.

Grading Policies

There will be 10 equally weighted assignments due on Canvas at 11:59 pm on Friday. Weekly summary sheets will be due in class on Thursday. Assignments can be found on the course website under schedule. Weekly assignments will be based primarily on the readings and class activities during weeks 1-5. During weeks 6-10 the weekly assignments will consist of a) readings and class activities and b) questions specific to student projects. Weekly assignments will assess the students progress on Learning Goals 1,2, 3, 4 and 6. The Weekly summary sheets align with Learning Goals 1, 2, 4, 5, and 6. The Final Presentation will assess the students’ competency in Learning Goals 3, 4, 5, and 6.

Weekly Assignments - 70%
Weekly Summary Sheets - 10%
Final Presentation - 20%

Course Schedule

The details course schedule is available on the course website at: https://sr320.github.io/course-fish274-2019/schedule.

Disclaimer: This syllabus represents my current plans and objectives. As we go through the quarter, those plans may need to change to enhance the class learning opportunity. Such changes, communicated clearly, are not unusual and should be expected.