DA 101 - Introduction to Data Analytics

Required Texts

Software

Grading and Feedback

Since there are multiple sections of DA 101 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. 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 give you a better idea of what it might mean to major in data analytics, as many of you are hoping to do. If you don't want to be a data analytics major, these criteria are still highly relevant to almost any program of study. 

Primary Assignment Rubric

Grading Scale

Grade Breakdown

The Quantitative GE Requirement

The goal of the quantitative reasoning requirement is to develop the skills of all students in the descriptive, analytical, and predictive aspects of quantitative reasoning. A course fulfilling this requirement must utilize numerical quantities and employ, as an integral and sustained part of the course, at least one of the following forms of quantitative reasoning.

1. the application of mathematical models to describe or predict the behavior of systems, and the design, construction, and interpretation of graphical representations of mathematical models.
2. the utilization, numerical analysis, and interpretation of the significance and limitations of data to answer questions, test hypotheses, or solve problems, and the design, construction, and interpretation of graphical representations of numerical data.

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.

Distractions

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. (Our lab will be completely remote and conducted in the same way.) 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.

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.

Teaching Assistants

Our TA for this section of DA 101 will be Lam Tran (tran_l7[at]denison.edu). Lam is a double major in data analytics and economics, with a minor in computer science, and she will graduate in Spring 2021. She has worked extensively in Python and R, and she experience with data visualization, data analysis, and database design. She will attend our weekly lab (remotely), and she will be available by appointment to help answer questions about the course or particular assignments. Her TA hours are Wednesdays, 9-10 p.m. and Thursdays, 6-7 p.m.. You can connect on Zoom on either day, and in person on Thursdays (in Burton D. Morgan 405). Lam's office hours are also posted on NoteBowl with a Zoom link and a Password. Office hours for all other DA 101 TAs will follow. While each TA is scheduled to work with a particular faculty instructor and attend their lab sections, our program encourages students to visit any TA during scheduled office hours, especially if their availability better fits your schedule.