Course Syllabus

Syllabus

CLIMATE/SPACE 423:

Data Analysis and Visualization for Geoscientists

Winter 2021 (4 Credits)

An Introduction to Data Analytics, Data-Model Metrics, and Plot Visualization for Climate and Space Scientists and Engineers

Course Description:

This is an upper level undergraduate course focusing on fundamental data science, data and error analysis, data-model comparison tests and metrics, and visualization techniques. The instructor will teach through a combination of lecture and interactive laboratory sessions from space and climate sciences using Python for analysis. While no prior experience with Python is required, basic familiarity with programming is highly recommended. The course will culminate in a final project with a dataset chosen by the students and guided by the instructor. By the completion of this course, students will be able to: read and write data sets using Python, perform large data set analysis, hypothesis testing and model goodness-of-fit quantification, and produce publication-ready scientific data visualization.

Instructor:

Dr. Mike Liemohn, Professor, Department of Climate and Space Sciences and Engineering

Room 1436, Climate and Space Research Building (on North Campus, 2455 Hayward St.), although this term in our fully remote configuration, I won’t be there very often

Email: liemohn@umich.edu

Instructional Aide:

Alex Shane, CLASP PhD candidate, adshane@umich.edu

Grader:

Brian Swiger, CLASP PhD candidate, swigerbr@umich.edu

Class Sessions:

Monday and Wednesday, 3:00 – 4:50 pm, fully remote

Office Hours (not held until second week):

Prof Liemohn: Tuesdays, 11 am – noon (most weeks, I will let you know when it shifts)

Mr. Shane: Mondays 11 am – noon

Also, both are available for appointment via email.

Textbook:

I am currently writing a textbook for this course. I will be distributing PDFs of the chapters throughout the term. I have most of the words but, as of mid-January, only a few of the figures are fully completed, embedded, and described. Any feedback and suggestions about the book are very welcome. In fact, there is optional extra credit available for providing this feedback. Please see below.

Other Useful Books:

For the first half of the course, the content is mostly from Taylor, and the second half of the course is mostly from Wilks. Another good one, for the programming aspects of the course, is the Python data science book by Igual and Segui.

Taylor, John R., An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements. Second Edition (1998). University Science Books.

Wilks, Daniel S., Statistical Methods in the Atmospheric Sciences, Academic Press. International Geophysics Series, Volume 100.

Igual, Laura, and Segui, Santi, An Introduction to Data Science A Python Approach to Concepts, Techniques and Applications, available online through the U-M library.

Additional Useful Online Resources:

Michigan Data Science Team (MDST) - holds weekly training mostly in Python as well as R - http://midas.umich.edu/mdst/
Michigan Institute for Data Science (MIDAS) - holds talks, classes, workshops etc http://midas.umich.edu/
Consulting for Statistics, Computing and Analytics Research (CSCAR) http://cscar.research.umich.edu/
Computational Social Science (CSS) - holds events, workshops, and trainings
https://sites.lsa.umich.edu/css/. Including the Ross Business School Big Data Camp at https://icosbigdatacamp.github.io/2018-summer-camp/

Grading Apportionment:

Midterm Exam: 10% (asynchronous limited-time exam)

Final Exam: 20% (asynchronous limited-time exam)

Homework: 50% (mostly weekly, due on Wednesdays before class)

First Project: 10% (Jupyter notebook and oral presentation)

Second Project: 10% (Jupyter notebook and oral presentation)

See the detailed day-by-day course outline below for the specific due dates of these assignments and exams. We expect to have 9 homework assignments. The first two will be a by-hand problems, mosty uncertainty propagation, but the others are programming assignments, submitting Jupyter notebooks with explanatory text and Python code. You might have some extra work to do in the “text” sections of the notebook. The final two “homework” assignments are peer-grading comments on the presentations of other students for the two projects. The projects are essentially homeworks, but this time with an oral presentation and flexibility on the topic and data set. Both the midterm exam and the final exam will be take-home tests, allowing a few days to get through it. Because of the well-being break in late February, the midterm is earlier than I planned but still works out pretty well.

Student Collaboration:

When doing homework assignments and projects, I encourage collaboration and peer tutoring. Please help each other learn the material and get through the work. You can even help each other edit and hone your Python code and oral presentations. When it comes to actually typing up the submission, though, I expect each of you to do your own work. You learn very little by copying another’s answers.

For the midterm and final exams, I am holding you to the Engineering Honor Code and expect that each of you will do your own independent work and submission without any input or aid from others. For these two grading elements, you should do it all yourself. Any questions should be directed to Prof. Liemohn, and if a class-wide clarification is needed, I will send out an announcement through Canvas.

Grading Breakdown:

This class will not be curved. The grades will be assigned as follows:

A+ 97% B 83% C- 70%

A 93% B- 80% D+ 67%

A- 90% C+ 77% D 63%

B+ 87% C 73% D- 60%

Normal rounding will apply, so a 96.50 is an A+ and a 96.49 is an A.

Late Policy:

Assignments, whether homework, projects, or exams, are expected to be submitted by 3:00 pm on the listed due date (just before class time, if it is a class day). Assignments submitted after ~3:15 will be considered late and reduced by 10%. After 7 days, or when we return the final grades on the assignment, whichever is first, the assignment will not be graded. Excused late submissions must be requested before the due date and time.

Extra Credit:

There will be opportunities for extra credit, one at the very end of the course and the others throughout the course.

The first (really, last) is turning in the receipt acknowledging that you filled out the course evaluation. If you upload a screen shot/pic/PDF of the page showing that you submitted it, then you will receive 1% extra towards your overall grade.

The second will be a written report evaluating the textbook draft. I would greatly appreciate any feedback and suggestions to make the book as good as possible. This will be done through 8 separate extra credit “assignments” in Canvas, one for each chapter. Each of these consists of a mix of Likert-scale agree-disagree responses with free-response entries to explain that response. I am making them due on Fridays. They will be open for another week past the nominal due date, but after that, then please comment on past chapters in the latest open book feedback questionnaire.

The extra credit assignments are optional. I value your feedback about the course and look forward to reading your comments on what went well and what could be improved. I strive to improve my teaching skills every term. Regarding the book, I want to make it as useful as possible. The feedback will not be seen by the grader for the course, so what you tell me about the book will not influence any other aspect of your course grade.

Religious Absence

Students who expect to miss classes as a consequence of their religious observance will be provided with a reasonable alternative opportunity to make up any missed academic work. It is the obligation of students to provide the instructor with reasonable notice of the dates on which they will be absent. We will determine a mutually agreeable make up opportunity within the boundaries of the class.

School-Function-Related Absence

If you are traveling with a U-M sports team or going to a research conference, we will make arrangements to accommodate missed academic work. It is the obligation of students to provide the instructor with reasonable notice of the dates on which they will be absent. We will determine a mutually agreeable make up opportunity within the boundaries of the class.

Disability Access

If you think you may need an accommodation for a disability, then please inform the instructor early in the term. You should contact the Services for Students with Disabilities (SSD) office to be issued a Verified Individual Services Accommodation (VISA) form, to be given to the instructor. We will do everything we possibly can to accommodate all such requests.

Student Mental Health and Wellbeing

If you or someone you know if feeling overwhelmed, depressed, and/or in need of support, then services are available. For help, please contact Counseling and Psychological Services (CAPS) at 734-764-8312 or online at https://caps.umich.edu. You may also consult University Health Service (UHS) at 734-764-8320 and at https://www.uhs.umich.edu/mentalhealthsvcs, or for alcohol or drug concerns, see www.uhs.umich.edu/aodresources. For a listing of other mental health resources available on and off campus, visit http://umich.edu/~mhealth/

Student Sexual Misconduct Policy

Title IX prohibits discrimination on the basis of sex, which includes sexual misconduct – including harassment, domestic and dating violence, sexual assault, and stalking. We understand that sexual violence can undermine students' academic success and we encourage anyone dealing with sexual misconduct to talk to someone about their experience, so that they can get the support they need. Confidential support and academic advocacy can be found with the Sexual Assault Prevention and Awareness Center (SAPAC) on their 24-hour crisis line 734-936-3333 and at https://sapac.umich.edu. Alleged violations can be reported to the Office for Institutional Equity (OIE) at insitutional.equity@umich.edu

CLIMATE/SPACE 423 Course Outline (Winter 2021)

Date	Style	Topic	Due (by 3 pm)
W Jan 20	Book Ch 1	Introduction to class and to uncertainties
M Jan 25	Book Ch 1,2	Calculating and propagating uncertainties	Pre-class survey
W Jan 27	Seminar	*Special seminar by Dr. Nicola Fox, 3:30 pm*
M Feb 1	Book Ch 2	More uncertainty propagation, special cases
W Feb 3	Coding	Basics of Python: opening files and making plots	HW #1
M Feb 8	Book Ch 3	Analysis of a single data set: histograms and basic stats
W Feb 10	Book Ch 3	Analysis of a single data set: special distributions	HW #2
M Feb 15	Book Ch 3	Analysis of a single data set: non-Gaussian distributions
W Feb 17	Coding	Multi-panel plots and datetime objects	HW #3
M Feb 22	Book Ch 4	Analysis of two data sets: scatterplots and correlations
W Feb 24	No class	No class, well-being break
F Feb 26	Due date	Midterm Exam due (assigned a few days earlier)	Midterm Exam
M Mar 1	Book Ch 4	Analysis of two data sets: curve fitting
W Mar 3	Coding	Data merging and indexing with spacecraft data	HW #4
M Mar 8	Book Ch 8	More visualization examples and discussion
W Mar 10	Coding	Groupby, Normal Distributions, & Boxplots	HW #5
M Mar 15	Book Ch 5	Data-model comparison: philosophy and basics
W Mar 17	Coding	Linear Regression & Geo-Mapping	HW #6
M Mar 22	Book Ch 6	Data-model comp: fit performance metrics; project #1 details
W Mar 24	Coding	Correlation and hypothesis testing	HW #7
F Mar 26	Due date	Project #1 check-in statements due	Proj 1 check-in
M Mar 29	Book Ch 7	Data-model comp: event detection metrics
W Mar 31	Coding	Object Oriented Programming and Bootstrap Analysis
M Apr 5	Due date	Project #1 presentations; project #2 details	Proj #1
W Apr 7	Due date	Project #1 presentations	Proj #1
M Apr 12	Coding	Image processing and calculating metrics – asynchronous	Proj 2 check-in
W Apr 14	Book Ch 8	Additional data analysis topics – *probably asynchronous*
M Apr 19	Due date	Project #2 presentations	Proj #2
W Apr 21	Due date	Project #2 presentations	Proj #2
M Apr 26	Due date	Final Exam due (assigned a few days earlier)	Final Exam

CLIMATE/SPACE 423: Data Analysis and Visualization for Geoscientists

Course Conduct Statement

Prof. Mike Liemohn liemohn@umich.edu

The College of Engineering has an honor code. This is taken seriously.

See the website: http://www.engin.umich.edu/students/honorcode/code/

Policy on Homework and Projects

You are encouraged to form study groups to work on homework problems and to study in other ways. You are allowed to consult with other students during the conceptualization of a problem. However, all written work, whether in scrap or final form, is to be generated by you alone. You are not allowed to possess, look at, use, or in any way derive advantage from the existence of solutions prepared in prior years, whether these solutions were former students' work product or copies of solutions that had been made available by others.

Policy on Exams

You are to complete all examinations on your own, with only benefit of the allowed aids (for this class...nothing), and without looking at or talking about the examination work of others. If you see a violation of the Honor Code, then you are obligated to report it.

For those needing special accommodations, please provide me with the proper form at least two weeks before the first exam so that arrangements can be made.

All of the exams are take-home tests and should not require an excused absence. If you know that you have a major conflict with one (due to athletic travel, religious observances, etc.), then please let me know at least two weeks in advance so that we can make arrangements. If you miss one due to a medical emergency, then you need a doctor's note explaining the situation.

On each exam, the Honor Pledge will be printed and you should sign your name under it. The Honor Pledge is as follows:

"I have neither given nor received unauthorized aid on this examination, nor have I concealed any violations of the Honor Code."

The Honor Council policy is that I am not required to grade tests in which the signed Honor Pledge does not appear. The Honor Code remains enforced whether or not the student signs the Pledge.

During an exam, email or see the professor with any clarifying questions you may have. If an answer to a question is relevant to everyone, then it will be sent via a Canvas announcement.

Violations

Violation of this policy is grounds for the initiation of a report filed with the Dean's office and the case would come before the Honor Council of the College of Engineering. If you have any questions about this policy, please do not hesitate to contact me.