DA 301 - Practicum in Data Analytics

Fall 2020

Your Professor:

Matt Lavin

My Email:


My Office:

Burton D. Morgan Center 411

Office Hours

MTWF 9:30-11 a.m.; MW 3:20-4:40 p.m.

Our Classroom:

Burton D. Morgan Center 219

When We Meet:

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

Course Description

Using Denison as a model of society, this practicum will analyze new and existing data sources at Denison to explore questions of collective importance. A problem-driven approach will lead students to synthesize and build upon data analytic skills from previous courses through a realistic, organic, and ethical context that carefully considers the implications of data communication (oral, visual, and written) and policy recommendations on a project for stakeholders and community members. A significant component of the course is collaborative with a small team of students working throughout the semester for a “client” usually from Denison or the surrounding community. This work will emphasize developing communication skills appropriate for the public and/or a private audience. Though a significant learning opportunity itself, this course should also be seen as a prelude to a community internship in the post-Junior year summer and will provide ample opportunities to develop a foundation for an intellectual and professional life after Denison. In this course, students will synthesize, hone, adapt, and translate their data analytics skills to a real problem, and be exposed to data analytics in a broad context (for profit, non-profit, government, academic research, and other disciplines).

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 MTWF 9:30-11 a.m. and MW 3:20-4:40 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. Since our class is team-based, we will likely use some of these appointments for an entire team at a time. 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.

Note about the Two Sections of DA 301

Dr. Michael Brady teaches the other section of DA 301 this semester. He will no doubt prove a valuable resource and sounding board throughout the class. His office is in Burton Morgan 401 and he can be reached at ​bradym[at]denison.edu

Required Texts

Selected readings will be made available as html or pdf, and linked to the course website (expect to spend a little more than normal on printing fees)
Self-directed reading as part of your project/client research
Recommended but not required: HBR Guide to Project Management, available on Amazon for less than $15. We'll read a few pdf excerpts from this book, but it's a really nice reference manual that you would benefit from owning.   

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. Particular clients may require you to work in certain languages, or with certain toolkits. Short of that, your top priority should select tools and approaches you know how to use, and/or tools and approaches that best fit the task. I will add that 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.)

Grade Breakdown

Item Percentage Comments
Team Projects 65% The largest portion of the class grade will be based on the ability of teams to work through the data analysis cycle, problem solve collaboratively, and produce a quality final product for their client to use.

Initial bid proposal


Bid proposal presentation


Technical progress report I


Technical progress report II


Project Final Packet

(Includes Executive Summary, Technical Report, Products, and Presentation and Debrief Components)

Individual Skill Building 35% A portion of the class grade will be based on individuals practicing and demonstrating mastery of technical and non-technical professional skills.
  10 Class participation
  10 Scaffolding assignments
  5 Domain-knowledge assignment
  5 Visualization assignment
  5 Ignite presentation


Project Information

The client-based course projects are designed to give you the opportunity to collaborate with a team and with an end user on a set of deliverables within a constrained timeline. The goals of the semester-long project include learning how to work on bigger, more open-ended data sets or analysis products, and to give you the opportunity to gain practical experience and expertise in using data analysis tools that you will need in the real world while you still have access to experienced teachers to help you navigate the process. While some class time will be provided to work on projects, you will need to schedule time to work within your teams outside of class. Your instructor and client will provide feedback at several points throughout the semester.

Grading and Feedback

Since there are two sections of DA 301, Dr. Brady and I haved worked hard to make sure there is approximate parity in terms of content, workload, and expectations. However, it is also true that we each have our strengths, areas of interest, and priorities. You will have to spend some time with me to get a real sense of what I value and how I grade, but I look forward to that process, and to getting to know you all better more generally. One of the big advantages of a school like Denison is that, if you want to work with me again, you'll probably be able to, whether in another data analytics course, a summer research fellowship, or some other capacity. 

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. I don't expect your work to meet the same standards as a graduating senior, but I think using the same categories on our rubric will help you track your progress over time. 

Primary 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.

Grading Scale

Letter Grade Percentile Description
A+ 97-100 Superior achievement in all aspects
A 94-96 Superior achievement in most areas
A- 90-93 Superior achievement in at least one area
B+ 87-89 Exceeds expectations in all aspects
B 84-86 Exceeds expectations in most areas
B- 80-83 Exceeds expectations in at least one area
C+ 77-79 Meets expectations in all aspects
C 74-76 Meets expectations in most areas
C- 70-73 Meets expectations in at least one area
D 65-69 Does the assigned task but does not meet expectations or work is not appropriate for college level
F 0-64 Unexcused late work, does not do the assigned task, not complete, or quality is significantly below expectations

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 particiation. 

Remote and Asynchronous Learning Policy

In these unprecedented times, our section of DA 101 will 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 or asynchronously, as long as they complete all the work for each day of class. I only ask that you keep me informed and meet with me and/or our TA, 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.

If you need to participate in a particular class remotely but synchronously, you can do so by joining the remote feed for our course, which will be password protected but online for every class period. If you need to participate in a particular class remotely and asynchronously, you will be able to access a video recording of the day's Zoom broadcast via Notebowl. You should also look at the daily calendar and complete any readings, quizzes, homework, lab reports, etc. If you are missing a team-based assignment, you should coordinate your participation with your teammates. To get access to any lectures, or to make up a peer review, you should email me about whether to make a virtual appointment with me or our TA.

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.

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.


Initial Bid Proposal (10% of course grade)

This team-based assignment responds to the client's Request for Proposal (RFP). In the simplest sense, a proposal is a plan of action for addressing a need. It is a specific genre in professional writing, which strives to be honest, evidence-based, specific, and detailed. Bid proposals typically include information about the company making the bid, the work to be performed, anticipated costs, a timeline of work to be done, a list of subcontractors to be included, and anything asked for in the RFP. Our proposals will be a little bit different since we are writing them for clients and for this class, but we will stay fairly close to a standard template. Read more about the assignment expectations for the Initial Bid Proposal.

Bid Proposal Presentation (5% of course grade)

In this team assignment, you and your teammates will first meet with and present to your client in detail, and then present an abbreviated summary of your project and approach to the class. All members of the team should participate in the presentation for roughly equivalent amounts of time. Read more about the Bid Proposal Presentation.

Technical Progress Report I (10% of course grade)

The main goal of the progress report is to demonstrate visibility and transparency to your client. You need to make sure they understand how the project is progressing and have the opportunity for input at critical checkpoints along the way. Read more about the first Technical Progress Report.

Technical Progress Report II (10% of course grade)

The main goal of this progress report is to update your client on the past month’s accomplishments and provide the opportunity for input on any changes or new insights thus far. Read more about the second Technical Progress Report.

Domain-knowledge Assignment (5% of course grade)

This individual writing assignment is meant to be a mini-review of a sub-topic related to your client’s field or project, to help each team member build domain knowledge, and to help each team assemble domain knowledge from complimentary areas. Read more about the Domain-knowledge Assignment.

Visualization Assignment (5% of course grade)

This individual writing and visualization assignment asks you to think deeply and critically about how to present visual information in ways that will ultimately inform your team's final project packet. Read more about the Visualization Assignment.

Ignite Presentation (5% of course grade)

A PechaKucha is a type of “lightning” talk that has gained in popularity across business, scientific, and academic worlds in the past ten years. We’re going to try the “Ignite” version of this format, which is even faster! In short, it is a 20X20 format with 20 slides, each of which is displayed for exactly 20 seconds. Read more about the Ignite Presentation

Final Project Packet (30% of course grade)

This team assignment is made up of written and verbal components. Through many individual and team assignments, we have already been working on many aspects of this packet. The initial bid assignment, domain knowledge assignment, technical progress reports, presentations, in-class workshopping, and visualization assignment all feed into this assignment. As a result, the written deliverables and subsequent presentation represent a culmination of all the work and skills that you have been building all semester! Read more about the Final Project Packet.

Summary of Due Dates

Due Date Assignment
Wednesday, August 19, 2020 Sign up for Github and share all Google Drive folders (s)
Monday, August 24, 2020 Team Norms Document; add details to your Github profiles (s)
Monday, August 31, 2020

Draft of Project Plan (s) and Resume (s) 

Monday, September 7, 2020 IRB Certificate (s) and Domain-knowledge Assignment (i)
Wednesday, September 9 Bid Proposal Presentations (t)
Sundat, September 13 Initial Bid Proposal (t)
September 14-18 Bid Proposal Presentations to Clients (t)
September 21 Github workshop (s)
Sept 28 Team draft visualizations (s)
October 2 Technical Progress Report I (t)
October 5-9 Team meetings with Dr. Lavin (s)
October 12 Individual Visualization Assignment (i)
October 23 Technical Progress Report II (t)
November 9 Ignite presentations 
November 11 Ignite presentations, peer review
November 20 Final project deliverables (t)
Exam Week Formal presentations to clients (t)

Weekly Calendar

Quarter 1

Week 1: Getting Started

Monday, August 17, 2020

In Class: Introductions, Syllabus, Teams and Clients

Homework: Read Project Management from Simple to Complex chapters 1-4. Sign up for Github accounts and share Google Drive folders (click link for directions).

Wednesday, August 19, 2020

In Class: Discuss readings, open time for teams to work, talk, and strategize.

Homework: Teams meet outside of class (in-person or on Zoom), begin discussing their project, and start writing out team norms in a google doc. By Monday, complete the team norms document, including electronic signatures of all team members. (Share Google folder with me to submit.)

Week 2: Project Management and Scope

Monday, August 24, 2020

In Class: Discussion of team norms, open time for teams; Fill in some details on your Github profiles, including profile photos. (Note: You are not required to share a photo of yourself if you don't want to. The idea here is just to replace the default profile photo with something more personalized.)

After Class: Send introductory email to client if you haven't yet done so.

Homework: Read about Scope Management (from the Software Project Manager's Bridge to Agility, 2008), read HBR Guide to Project Management chapters 5 and 6 (on NoteBowl)

Wednesday, August 26, 2020

In Class: Discussion of professional writing practices, open time for teams

Homework: Submit draft for project plan in team Google Drive folder (directions in NoteBowl under Documents); Submit team member resumes in individual Google Drive folders

Week 3: Time, Quality, Risk, and Ethics

Monday, August 31, 2020

In Class: Data documentation worksheet, open time for teams

Homework: Read Project Management from Simple to Complex chapters 8, 10, and 11, and the Data Science Code of Professional Conduct

Wednesday, September 2, 2020

In Class: Discuss readings, ethics in data science

Homework: By Friday, September 4, add IRB certificates to individual Google Drive folders

Homework: By Monday, submit domain knowledge assignment to individual Google Drive folders and read Project Management from Simple to Complex chapters 5 and 6, Dealing with Disruptive Behaviors, Linux Foundation Data Values and Principles

Week 4: Teamwork, Meetings, Handling Conflicts

Monday, September 7, 2020

In Class: Discuss readings and Initial Bid Proposal assignment (due Friday)

Homework: Finish bid proposal presentations, submit via team Google Drive folders

Wednesday, September 9, 2020

In Class: Bid proposal presentations, feedback from classmates

Homework: Initial Bid Proposals added to team Google Drive folders and and emailed to clients by Sunday at 5 p.m. EST (cc Dr. Lavin)

Quarter 2: 

Week 5: (Bid Proposal Presentations to clients should happen this week)

Monday, September 14, 2020

In Class: Begin discussing research design, open time for teams

Homework: Read research methods pt1 (on NoteBowl)

Wednesday, September 16, 2020

In Class: Project sprints 

Homework: Read research methods pt2 (on NoteBowl)

Week 6: Version Control and Data Visualization

Monday, September 21, 2020

In Class: Git and Github Workshop (documentation and collaboration)

Homework: Read Cairo, The Truthful Art, 41-65 (NoteBowl)

Wednesday, September 23, 2020

In Class: Data Visualization 

Homework: Create draft visualizations. Each team should have two charts/graphs to present and workshop with the class. Submit via team Google Drive folders. 

Week 7: Data Visualization Continued

Monday, September 28, 2020

In Class: Data visualization workshop

Homework: Meet with teams outside of class, work on Technical Progress Report I

Wednesday, September 30, 2020

In Class: Markdown; Team check-ins and project sprints for Technical Progress Report I

Homework: By Friday, complete Technical Progress Report I. Submit via team Google Drive folders. Email to client (cc Dr. Lavin)

(10/3-10/4 is No-work Weekend)

Quarter 3:

Week 8: (Team meetings with Dr. Lavin happen this week)

Monday, October 5, 2020

In Class: Mid-term Evaluation and Progress Report, and project sprints

Homework: Attend team meeting with Dr. Lavin

Wednesday, October 7, 2020

In Class: Project sprints

Homework: Complete Individual Visualization Assignment and submit to individual Google Drive folders

Week 9: Communication Part I

Monday, October 12, 2020

In Class: Jupyter Notebooks; check-ins, project sprint time

Homework: Touch base with clients, ask if a meeting is desired

Wednesday, October 14, 2020

In Class: Check-ins, project sprint time

Homework: Read read HBR Guide to Project Management chapters 13 and 17 (on NoteBowl); meet with teams outside of class

Week 10: Communication Part II

Monday, October 19, 2020

In Class: Discuss effective team communication; check-ins, project sprint time

Homework: Read excerpt from Steven Pinker, A Sense of Style (NoteBowl)

Wednesday, October 21, 2020

In Class: Discuss communicating for genre and audience

Homework: By Friday, October 23, complete Technical Progress Report II. Submit to team Google Drive folder. Email to client (cc Dr. Lavin)

Quarter 4: 

Week 11: Getting Results

Monday, October 26, 2020

In Class: Check-ins, project sprint time

Homework: Meet with teams outside of class

Wednesday, October 28, 2020

In Class: Check-ins, project sprint time

Homework: Keep working on project deliverables

Week 12: Improving Results

Monday, November 2, 2020

In Class: Check-ins, project sprint time

Homework: Meet with teams outside of class

Wednesday, November 4, 2020

In Class: Refactoring; check-ins, project sprint time

Homework: Finish Ignite Presentations and submit on Notebowl

Week 13: Communicating Results

Monday, November 9, 2020

In Class: Check-ins, project sprint time

Homework: Complete presentation peer reviews

Wednesday, November 11, 2020

In Class: Check-ins, project sprint time

Homework: Read Project Management from Simple to Complex chapter 14

Week 14: Product Completion and Deliverables

Monday, November 16, 2020

In Class: Discuss project closure; complete course evaluations

Homework: Meet with teams outside of class

Wednesday, November 18, 2020

In Class: Check-ins, project sprint time

Homework: By Friday, November 20, complete Final Project deliverables. Submit to team Google Drive folders. Please read the full instructions very carefully, as I would hate to find that I am missing any final project components. 

Thanksgiving Break

Monday, November 23-27, 2020

Week 15: Remote Finals Week

Monday, November 28, 2020

Reading and Study Day

Tuesday, November 29, 2020

Reading and Study Day

November 30, 2020 - December 3, 2020

Final Exams: Formal presentations to clients and debriefing -- scheduling these will be challenging and in concert with clients and students from the other section of DA 301. These will be done remotely, but asynchronous participation will not be possible.