DA 401 - Seminar in Data Analytics

Spring 2021

Your Professor:

Matt Lavin

My Email:


My Office:

Burton D. Morgan Center 411

Office Hours

MW 3:30-5:00 p.m.; Th 1:00-3:00 p.m.; F 1-2 p.m.

Our Classroom:

Burton D. Morgan Center 315

When We Meet:

MW 1:50-3:10 p.m.

Course Description

DA 401 is a capstone seminar for the Data Analytics major in which students work on independent research projects in a collaborative seminar setting. The seminar is the culmination of the Data Analytics major, a showcase for the problem-driven display of analytic, statistical, and programming skills through an independent research project. It is heavily focused on and invested in communicating data anlytics research in the form of an oral presentation and a written paper that meets the standards of professional and scholarly audiences to a level expected of graduating seniors in data analytics. 

Students' research questions may originate from internship experiences, courses of study at Denison, or other sources, subject to the instructor's approval. In all cases, students’ individual projects will build upon their entire skill set and domain concentration in a complete research project that synthesizes and hones pre-existing skills, develops new project specific techniques, generates deeper domain knowledge, and professionally shares the results through written, visual, and oral communication. Since the topics will vary widely based on student choice, class sessions will resemble workshopping and brainstorming sessions commonplace in research hubs, where peers provide assistance and feedback as projects develop. Assigned readings (to be completed outside of class) will supplement this work by focusing on research design concepts and strategies for effective presentation of quantitaive information. 

Last but not least, significant feedback on writing is a core component of this course. Students must present well, but also engage with their peers in substantive, constructive ways which maximizes the collaborative nature of research. Students are expected to review instructor and peer feedback and incorporate that into their future work.

Prerequisites: For Senior Data Analytics majors only. DA 301, DA 350, CS 181, Math 220, a disciplinary research methods course, and completion of an approved DA summer experience.

Office Hours

Note that I am not planning to do "in-person" office hours this semester. I am using Google Calendar for virtual office hours, by appointment. If you go to my appointment page, you will see a real-time account of when I am available. My standard appointment slots are MW 3:30-5:00 p.m.; Th 1:00-3:00 p.m.; and F 1-2 p.m.. Note that these appointment slots will disappear once I've been booked. If I ever need to cancel office hours on a given day (say, for example, if I'm ill), I will update the calendar and email anyone with an appointment. If I find that I have more requests for appointments than I have availability, I may convert some of these slots to virtual hangouts, where anyone would be welcome to drop in, but for the moment I will hold these as opportunities for one-on-one discussion. 

If my office hours by appointment do not work for your schedule, you can also email me to request an appointment at another time. When sending me such an email (or really any email), please follow some basic conventions of formality and politeness. There's no need to construct the equivalent of a business letter, but please don't begin your message with "hey," and please take an extra moment to make sure you spelled my name correctly. I promise to show you the same courtesy. I will do my best to reply within 48 hours, barring any emergency circumstances.

Additional Norms and Policies

Here you will find information on required readings, import university policies, and course-specific policies like attendance and cell phone use.

Required Texts

The Chicago Guide to Writing about Numbers Second Edition (Jane E. Miller), ISBN-13: 978-0-226-18577-4
Purchase at the book store or order online by matching the ISBN
Additional selected readings will be made available as html or pdf, and linked to the course website or shared via Notebowl

Computers and Software

Computers: Students are required to provide their own laptops and to install free and open source software on those laptops. Support will be provided by the instructor in the installation of any useful or required software. R can also be accessed via the browser at ​r.denison.edu​. If at any time you don’t have access to a laptop please contact the instructor and the Data Analytics Program can provide you with a loan from the laptop cart. In class, ​please use eduroam​ to connect to the Internet instead of Denison Guest. Please be respectful with your use of laptops and technology in class. I request that you only use them for class related purposes, as I and others may find them distracting (For example, ​no email or social media should be open in your browser tabs!). Cell phones should be kept silent and put away.
Github, Programming Languages, Software: We will be using git and Github for version control and collaboration. Other than that, this course is largely software agnostic, which is to say that you can use any programming language (r, python, javascript, etc.), digital tool (tableau, excel, minitab, etc.), or combination of languages and tools. Your top priority should select tools and approaches you know how to use, and/or tools and approaches that best fit the task. That said, I am assuming that most of you will use R or Python for most of your work, and I've asked you say so in the course syllabus if you plan to reply heavily on anything else. I am best equipped to give hands on assistance with python, jupyter notebooks, mysql/sqlite, r, html/css/javascript, markdown, and Docker, so please do keep that in mind. (I'll make every effort to help with other languages and software, but you should know what my strengths are.)

Grading and Feedback

Since there are multiple sections of DA 401 every semester, the various instructors work hard to make sure there is approximate parity in terms of content, workload, and expectations. However, it is also true that each professor has their strengths, areas of interest, and priorities, and I'm sure I'm no exception. We'll have to spend some time together for you to get a real sense of what I value, how I grade, etc., but I look forward to that process, and to getting to know you all better more generally.

As a general rule, the expectations in this course are high, and I'm confident you can all do great work. The feedback I provide on assignments is designed to help you get there. My goal is to provide specific, relevant, and honest feedback when I grade your work. This will include constructive criticism, strategies for improvement, and guidance on how students can achieve success. I will not do "compliment sandwiches" just to begin and end on a positive remark, but this means that, when I praise your work, it's an honest (and I think more meaningful) act of praise. 

Regarding the major assignment rubric, it is adapted from the standards that the data analytics program uses for all its majors.

Major Assignment Rubric

Item Description
Assignment Process: All materials are turned in on time and in the right place. Assignment directions are followed. Required components are all present and submitted on time.
Attention to Detail: The project is well organized, flows logically, and follows the all formatting guidelines, including attention to proofreading, proper citations, and language that is appropriate to a well-informed, non-technical reader.
Research Question and Research Design: The project has a focused and well defined research question that can be addressed with computational, data-driven analysis. The focal data set and method(s) are appropriate for the research question.
Data, Visuals, and Code: The data are fully described, properly sourced, and presented in appropriate ways. Visuals (tables, charts, graphs) are used effectively to describe multiple aspects of the research project (data, methods, or results). The paper provides sufficient details and/or points to supplementary materials that make the research reproducible by a technical reader (i.e, detailed footnotes, appendices, GitHub, code, etc.)
Data Analysis Methods: The method(s) used to test the research question is justified, validated, and applied appropriately; the student appropriately describes the strengths and weaknesses of the methods used; outside sources are used to justify how the methods are used and interpreted.
Reporting and Interpretation of Results: The results are interpreted correctly and clearly address the research question; the project discusses its limitations, the extent to which it can be generalized, and expansion to further research.
Ethical Considerations: The writing thoughtfully engages any ethical considerations of using the data, methods, and implications of communicating the findings.

Grade Breakdown

Item Percentage Comments
Proposal 5  
Domain knowledge + skill review 10  
Research design 5  
Early results 10  
First draft 15 Individual assignment. Four separate components (see assignment description)
Manuscript peer review 5  
Executive summary 5  
Presentation 15 Video submissions via Notebowl
Final draft 20  
Scaffolding assignments and seminar participation 10 Various assignments noted on syllabus and in Notebowl

Extensions Policy

Retroactive and last-minute extensions will not be granted. At the same time, life happens. Sometimes something just isn’t going to get done. If you speak to me at least a week ahead of time and I approve an extension, I will consider assigning a new due date and hold you to it. The trade off is that work turned in this way is probably not going end up in my hand when I grade everything else, so it’s going to get less feedback. If you miss a deadline entirely without getting an extension, you will automatically receive a 0 for your grade.


Cell phones should be off and put away. Laptops are okay for notes and such, but you should not be messaging, using Facebook, etc. I’ll check screens regularly give you a verbal warning on your first offense. After that, I reserve the right to ask you to leave class and mark you absent if you are creating a distraction.

Being Prepared for Class

Coming to class prepared means that you have the day's reading in hand (printed or digital) and have come to class with a way to take notes (printed or digital). If you are not prepared for class, I reserve the right to grade as if you were absent for that day. Anything due on a given day is due at the start of class. Any digital submission of material is due by the time class starts on the day the hard copy is due. These policies apply for in-person and remote participation.

Transitional and Remote Learning Policy

This class has a transitional learning policy, which means that we will conduct class over Zoom for the first several weeks (up to four weeks but not more than that) and then convert to an in-person course for all those willing and able to attend in person. Our section of DA 401 may have student participants in various locations and time zones. We can also expect that one or more students may need to miss class because of illness or quarantine protocol. As a result, there will be a no-permission-needed policy of allowing students to participate remotely. Do this by logging into Zoom in lieu of attending class. This section of DA 401, however, will require synchronous participation. That is, all students, regardless of time zone, will be expected to log in live for class. I also ask that you keep me informed and meet with me over Zoom, as needed, in order to keep apace with the course work. Note, however, that Denison's university-wide attendance policy still applies. This means, among other things, that if a class is missed, for any reason, the student is responsible for determining what occurred in the missed class. Additionally, absence from a class will not be accepted as an excuse for not knowing class material. Video recordings of past classes will be kept on Notebowl in case you are too ill to sign on synchronously, but these should be considered an option of last resort.

If all classes, at some point in the term, are forced to switch entirely to remote learning, I will provide detailed instructions on how to complete all the remaining assignments.

Disability Resources

If you are a student who feels you may need an accommodation based on the impact of a disability, you should contact me privately as soon as possible to discuss your specific needs. I rely on the Academic Resource Center in 020 Higley Hall to verify the need for reasonable accommodations based on documentation on file in that office.

Academic Integrity

Proposed and developed by Denison students, passed unanimously by DCGA and Denison’s faculty, the Code of Academic Integrity requires that instructors notify the Associate Provost of cases of academic dishonesty. Cases are typically heard by the Academic Integrity Board, which determines whether a violation has occurred, and, if so, its severity and the sanctions. In some circumstances the case may be handled through an Administrative Resolution Procedure. Further, the code makes students responsible for promoting a culture of integrity on campus and acting in instances in which integrity is violated.

Academic honesty, the cornerstone of teaching and learning, lays the foundation for lifelong integrity. Academic dishonesty is intellectual theft. It includes, but is not limited to, providing or receiving assistance in a manner not authorized by the instructor in the creation of work to be submitted for evaluation. This standard applies to all work ranging from daily homework assignments to major exams. Students must clearly cite any sources consulted--not merely for quoted phrases, but also for ideas and information that are not common knowledge. Neither ignorance nor carelessness is an acceptable defense incases of plagiarism. It is the student’s responsibility to follow the appropriate format for citations. Students should ask their instructors for assistance in determining what sorts of materials and assistance are appropriate for assignments and for guidance in citing such materials clearly.

Our Commitment to Liberal Arts Education

Denison's mission statement articulates an explicit commitment to liberal arts education. It emphasizes active learning, which defines students as active participants in the leaning process, not passive recipients. Denison seeks to foster self-determination and to demonstrate the transformative power of education. A crucial aspect of this approach is what Denison's mission statement refers to as "a concern for the whole person," which is why the university provides a "living-learning environment" based on individual needs and an overriding concern for community. This community is based on "a firm belief in human dignity and compassion unlimited by cultural, racial, sexual, religious or economic barriers, and directed toward an engagement with the central issues of our time."

In this class, we will discuss inequality directly. In many cases, you will asked to apply quantitative reasoning skills to these subject, which can be difficult because there is always the potential for the available data to complicate or contradict something you may feel very passionate about. In these cases, you should aspire to adopt an attitude of critical skepticism, i.e. wary of claims that are not supported by evidence but potentially willing to be persuaded by evidence if you find it compelling, and willing to give that evidence a fair hearing.

How we treat one another will be a cornerstone of these conversations. Denison's "Guiding Principles" speak of "a community in which individuals respect one another and their environment." Further, "each member of the community possesses a full range of rights and responsibilities. Foremost among these is a commitment to treat each other and the environment with mutual respect, tolerance, and civility." It's easy to treat someone this way when you like them and agree with their ideas, but the real challenge is treating those who differ from us with the same compassion and respect. However, I consider disruptive, deceitful, or hateful behavior to be breaches of these responsibilities. Bullying, trolling, hate speech, and harassment of any kind will not be tolerated.


Proposal (5% of total grade)

This document will perform two functions. First, the leading paragraphs identifies a scholarly conversation, methodological and/or domain-specific, and demonstrates that you have done enough preliminary research to understand this conversation and enter it. In a second (and sometimes third) paragraph, your proposal lays out your initial plans for intervening in the scholarly conversation you have identified. This includes establishing your central focus and your research question, as well as a statement on why this question is important. It should include key concepts (and perhaps measures) and lay out a preliminary sense of how the research might be conducted.

Domain knowledge + skill review (10% of total grade)

A mini review paper that can stand on its own (not a rundown of your specific study or planned methods), describing the landscape of the field to which your work should apply, or from which your method or idea originates. Includes a reflection on the skills you already have and need to develop in order to carry out your plan.

Research design (5% of total grade)

This short paper should build on your domain knowledge and skill review and link the research question to a logic of inquiry that states your design, measurement, and statistical choices. In essence, this is your preliminary methods section for your final research paper, but it will be graded separately.

Early results (10% of total grade)

This short paper should summarize your early findings. The focus is on communicating an early concrete story, effectively translating your visuals and quantitative data and analysis. In order to succeed on this assignment you will need to demonstrate significant progress on your project analysis, including completion of all data preparation and fully written, functional code.

1st draft (15% of total grade)

This draft of your seminar paper should be a complete draft (i.e., all sections written out) but will inevtiably be revised based on peer and instructor feedback.

Manuscript peer review (5% of total grade)

Detailed, constructive feedback on a classmate's first draft. (Partners will be assigned by the professor.)

Executive summary (5% of total grade)

Includes an overview of the question and its stakes, the logic of inquiry and its limitations, the essential findings, and the implications along with appropriate qualifications.

Presentation (15% of total grade)

Remote pre-recorded video presentations that distill the essential ingredients of the research rather than incorporating every detail of it. These video overviews should cover the research question, the logic of inquiry, your results, the implications of your work, and any appropriate qualifications to your conclusions.

Final draft (20% of total grade)

Submission of this assignment will include a detailed response to your peer review comments, as well as a fully polished and in every possible sense completed version of your seminar paper.

Scaffolding assignments and seminar participation (10% of total grade)

This includes attendance, participation, and smaller in-class or take-home assignments that will be required from time to time. Any such assignments will be noted on the weekly calendar.

Weekly Calendar

Week 1: Research Questions

Monday, February 01, 2021

In Class: Introductions

Homework: Complete course survey, read Miller Chapter 1 (on Notebowl)

Wednesday, February 03, 2021

In Class: Discuss reading

Homework: read Creswell Chapter 7 (on Notebowl)

Week 2: Brainstorming and Project Planning

Monday, February 08, 2021

In Class: Discuss reading; in-class brainstorming activity

Homework: Read Miller Chapter 2 (on Notebowl)

Note: By now, you should have purchased your own copy of the required book. Future reading assignments from Miller will assume you have your own copy.

Wednesday, February 10, 2021

In Class: Discussion of Miller Chapter 2

Homework: Scaffolding Assignment

Week 3: Project Proposals, Abstracts, and Literature Reviews

Monday, February 15, 2021

In Class: Project Planning Activity

Homework: Read Miller Chapter 3

Wednesday, February 17, 2021

In Class: Discuss Miller Chapter 3

Homework: Submit Proposal First Draft by Friday at 5 p.m. (on Notebowl); for Monday, read Creswell Chapter 1 (on Notebowl)

Week 4: Building Domain Knowledge

Monday, February 22, 2021

In Class: Discuss Creswell Chapter 1, "The Selection of a Research Approach"; Discuss How to Read and Take Notes

Homework: Scaffolding assignment on preliminary research

Wednesday, February 24, 2021

In Class: In-class scaffolding activity on preliminary research

Homework: Read Creswell Chapter 2, "Review of the Literature" (on Notebowl)

Week 5: Research Design

Monday, March 01, 2021

In Class: Discuss Creswell Chapter 2, "Review of the Literature"

Homework: Read Miller Chapter 4, "Five More Technical Principles" (book purchase required)

Wednesday, March 03, 2021

In Class: Discuss Miller Chapter 4, "Five More Technical Principles"

Homework: Turn in Domain Literature Review with Skills Section by 5 p.m on Friday, March 5, 2021

Week 6: Methods Part 1

Monday, March 08, 2021

In Class: In-class scaffolding activity on student methods

Homework: Read Miller Chapter 5, "Basic Types of Quantitative Comparisons" (book purchase required)

Wednesday, March 10, 2021

In Class: Discuss Miller Chapter 5, "Basic Types of Quantitative Comparisons"

Homework: Submit Research design by 5 p.m. Friday, March 12, 2021

Week 7: Data Set Development, Ethical Considerations, Data Management

Monday, March 15, 2021

In Class: Discuss ethical statement and protocols; IRB certification, application, or approval(s)

Homework: Read Miller Chapter 8, "Choosing Effective Examples and Analogies" and Chapter 9, "Writing about Distributions and Associations" (By Monday March 22)

Wednesday, March 17, 2021

No Class

See Monday's Homework; complete IRB requirements if applicable

Week 8: Preliminary Results

Monday, March 22, 2021

In Class: Discuss Miller Chapters 8 and 9; form groups for student-selected articles

Homework: Read Miller Chapter 10, "Writing about Data and Methods"; submit ranked lists for student-selected articles

Wednesday, March 24, 2021

In Class: Discuss Miller Chapter 10, "Writing about Data and Methods"

Homework: Submit Early results by 5 p.m. on Friday, March 26, 2021

Homework: Read Miller Chapter 6, "Creating Effective Tables" and Chapter 7, "Creating Effective Charts"

Week 9: Communicating Results, Data Visualization

Monday, March 29, 2021

In Class: Discuss Miller Chapters 6 and 7

Homework: Read Student Selected Articles 1

Wednesday, March 31, 2021

In Class: Discuss Student Selected Articles 1

Homework: Read Miller Chapter 11, "Writing Scientific Papers and Reports"

Week 10: Communicating Results, Written Communication

Monday, April 05, 2021

In Class: Discuss Miller Chapter 11, "Writing Scientific Papers and Reports"

Homework: Read Student Selected Articles 2

Wednesday, April 07, 2021

In Class: Discuss Student Selected Articles 2

Homework: Read Student Selected Articles 3

Week 11: Completing a Project to the Standards of Professional and Scholarly Audiences

Monday, April 12, 2021

In Class: Discuss Student Selected Articles 3

Homework: Read Student Selected Articles 4

Wednesday, April 14, 2021

In Class: Discuss Student Selected Articles 4

Homework: Submit First draft by 1:50 p.m. on Wednesday, April 21, 2021; Post Code and Data (or Simulation Data) to Github by start of class on Wednesday, April 21.

Week 12: Replication and Code Review

Monday, April 19, 2021

In Class: No class

Homework: See above

Wednesday, April 21, 2021

In Class: Code and documentation

Homework: Submit Manuscript peer review by 1:50 p.m. on Monday, April 26, 2021

Week 13: Replication and Code Review

Monday, April 26, 2021

In Class: In-class scaffolding activity on replication

Homework: Scaffolding assignment on executive summaries

Wednesday, April 28, 2021

In Class: In-class scaffolding activity (workshop executive summaries)

Homework: Submit Revised Executive summary by 5 p.m. on Friday, April 30, 2021; Submit Presentation Video by 5 p.m. on Sunday, May 2, 2021

Week 14: Peer Review and Final Presentations

Monday, May 03, 2021

In Class: Watch and Discuss Final Presentations

Homework: Submit questions for video presentations by 5 p.m. on Tuesday, May 04, 2021

Wednesday, May 05, 2021

In Class: Watch and Discuss Final Presentations

Week 15: Exam Week

Wednesday, May 12, 2021

Complete and Submit Final Version of Final Written Projects by 11:59 p.m. EST