MATH:3900 Introduction to Mathematics Research:

Data Visualization with TDA Mapper

Spring 2018 11:00A - 12:15P TTh 105 MLH

Instructor:  Dr. Isabel K. Darcy,  Department of Mathematics, AMCS, and Informatics, University of Iowa
Office:B1H MLH
Phone: 335- 0778
Email: isabel-darcy AT uiowa.edu

Tentative Office hours: Tuesdays/Thursday 8:50 - 9:15am, 12:30 - 1:35pm and by appointment.

TA: Wako Bungula
Office: 325L MLH
Office hours: TBA and by appointment.
Email: wako-bungula@uiowa.edu

DEO Contact Information: Maggy Tomova, 14 MLH, maggy-tomova@uiowa.edu

Course website (including schedule): http://homepage.divms.uiowa.edu/~idarcy/COURSES/TDA/SPRING18/3900.html

Course Description: Research experience; students study an elementary topic of active research, then work either individually or in groups under faculty supervision. The Spring 2018 course will focus data visualization with TDA mapper. The Spring 2018 Math 3900 course can be counted as a level 2 LDA certificate course.

Prerequisite: Linear algebra OR consent of instructor. Note this is an interdisciplinary introduction to research course, and thus students from a wide variety of backgrounds are encouraged to take this course. We definitely won't avoid math, but we will cover all needed background to understand data visualization with TDA mapper. A couple of lectures will use linear algebra, but we will use a visual approach and a thorough understanding will not be required due to the interdisciplinary nature of this course.

Objectives and Goals of the Course: To learn introductory research skills in data analysis and visualization. Students will be graded (as described below) based on points earned. Students can choose from a variety of ways to earn points and thus objectives and goals may be individualized to meet the interests and background of each participant. Some standard goals include:

For those interested in continuing this research or conducting research in another area in the summer or during the following academic year, one can apply to get paid to do research. For example:

Texts: None

Grading system:

In order to meet the interests and background of each participant, grades will be based on a point system as opposed to percentages. Each point you earn will be added to your grade. You can earn points via HW, quizzes, exam, and project(s), etc.

Quizzes and Homework (approximately 100 points possible)

Midterm: 50 points. Tentative date: Thursday March 8.

We will not have a final exam.

Presentations (up to 150 points): We will have mini-presentations during week 7 as well as project presentations during week 15. You are also encouraged to give additional presentations both in class as well as outside of class as described here

Project: Points will be earned throughout the semester. I would expect a standard excellent class project would earn 250 points total, but a truly exceptional project could earn 500 points (but only 500 are needed for an A).

Note you will be turning in parts of your project throughout the semester and thus you will be earning points throughout the semester toward your project grade. Most Thursdays we will meet in a computer lab (B5 MLH). Many of these labs will be incorporated into your project.

While students are encouraged to work in groups, each student will be graded individually as described on the project webpage.

Most, if not all, projects will focus on analyzing data; but other ideas are welcome.

Please let me know if you would like to earn points using other methods (e.g. creating software, writing teaching materials, etc.).

The following grades can be earned via the following combination of points. Collaboration is encouraged on everything except quizzes and midterm.

Grading system (see note below regarding class attendance) :

NOTE regarding class attendance: Class attendance is required, but if you need to miss a class, you can make up the class (for example by completing the lab if you miss a lab day, summarizing the missed lecture notes, or summarizing a video or part of a paper or book chapter).

This course will be individualized to meet the interests and background of each participant, so if you would like to propose your own individualized grading system, please let me know.

Student Collaboration: You are encouraged to collaborate with other students on homework and projects.  Copying is not collaboration and will be prosecuted under scholastic dishonesty.  Any significant collaboration should be acknowledged.

The University policies on scholastic dishonesty will be strictly enforced.

Resources for Students:

Students may find the Writing Center and the Speaking Center very useful for this course:

From Writing Center website: Suggestions and feedback on all kinds of writing, from course papers to creative pieces and multimedia projects.

You can obtain feedback via individual appointments, online submissions or weekly appointments (for weekly appointments, space is limited so sign up NOW if you are interested).

From Speaking Center website: We work with a range of students from many disciplines on such issues as: effective participation in class discussions, crafting and delivering oral presentations, understanding unfamiliar cultural references, interview skills, creative performances, and speech anxiety.

The College of Liberal Arts and Sciences Policies and Procedures