DS 200, Spring 2020: Introduction to Data Sciences

Section 002

This online document is the official course syllabus.
It is found at http://stat.psu.edu/~dhunter/200DS/index.html

Any changes made to the syllabus during the semester will be announced in class and appear in this document in red.

COURSE SCHEDULE
       Lectures: TuTh 1:35-2:50pm, 105 Osmond
       Labs: W 11:15am-12:05pm, 064 Willard
       Office Hours:M 4:00-5:00pm and Th 8:00-9:00am, 310 Thomas
       Tutoring Hours:WTh 7:00-10:00pm, E165 Westgate

TEACHING TEAM
    Instructor:
       David Hunter, 326 Thomas Building, dhunter@stat.psu.edu
    Learning Assistant:
       Ian Hoaglund, ibh5039@psu.edu

OVERALL COURSE GOALS
DS 200 will

"Statistical thinking skills" in this context are describing data, using data to make predictions, and inferring properties of a population from a sample.

REQUIRED COURSE MATERIALS

GRADING Learning outcomes will be assessed based on performance in each of the following categories accompanied by their impact on the overall grade:

Category Percent of Total Grade
Engagement 5%
Labs 30%
Homework/Quizzes 20%
Project 25%
Midterm Exam 20%
Final Exam 0%

Final letter grades will be determined as follows after rounding to the nearest whole number percent:
  B+: 88-89% C+: 78-79%  
A : 94-100% B : 84-87% C : 70-77% D : 60-69%
A-: 90-93% B-: 80-83%   

COMPONENTS OF OVERALL GRADE
Engagement: Historically, this component of the grade was simply the "clicker" grade, satisfied by coming to class and using your i>clicker. However, the use of clickers is designed to promote active learning in class, not to force students to come to class who really do not want to be there and would prefer to learn on their own outside of class. If the idea of using clickers in class sounds good to you, this is still an option; but there are several ways to earn points toward your engagement grade, which consists of a maximum of 18 points.
OPTION 1: Click in with your i>clicker during lecture. Each non-exam class is worth 1 point. You get credit as long as you click in to most of the questions, regardless of whether or not you answer correctly. Again, the main purpose of clickers is to stimulate thought and help you learn by giving you and me a sense of which concepts might be tricky and needing reinforcement.
OPTION 2: Demonstrate engagement by analyzing some of the datasets in this class beyond the course requirements. How this engagement will be demonstrated, and how far beyond the requirements one must go in order to earn engagement credit, is yet to be determined; yet the course philosophy is that an entrepreneurial spirit on the part of students will somehow be rewarded.
OPTION 3: There may be occasional opportunities to earn engagement points through special assignments. Such opportunities will be announced if and when they arise.

Labs: Labs are Wednesdays in 064 Willard Building. It is the labs where we will primarily address the course goal of requiring students to apply data science skills to problems derived from multiple application areas, among others of the course goals. We will use the python programming language in the labs, but we will do so in a somewhat sheltered environment and, in particular, no prior experience with coding or data analysis is assumed. Labs will entail occasional assignments that will be turned in and graded on Canvas. Late lab assignments are accepted for half credit up until it is one week overdue or until the final exam, whichever comes first.

Homework: There will be occasional homework assignments that will be assigned and turned in via Canvas. Late homework is accepted for half credit, up until the first exam on that material.
You may collaborate on homework and labs (this is encouraged!), but we recommend trying problems on your own first to prepare you for exams. Also, the work you turn in must be your own. In other words, if you work with other people to understand concepts, then each of you is responsible for submitting his/her own unique work.

Project: The semester project provides an opportunity to combine mutliple aspects of the course material and apply them to a large dataset.

Exams: There will be two midterm exams in class and a final exam. These exams will be closed to all materials except for a non cell-phone calculator and one (Exam 1), two (Exam 2), or three (Final) single-sided 8.5 by 11 inch pages of notes. Exams are mandatory, and must be taken at the given time. Unavoidable legitimate reasons for not being able to take the exam must be submitted to and approved by Dr. Hunter at least 24 hours before the beginning of the exam. Excuses submitted less than 24 hours before the exam might not be accepted.

ACACEMIC INTEGRITY POLICY
All Penn State and Eberly College of Science policies regarding academic integrity apply to this course. See http://science.psu.edu/current-students/Integrity/Policy.html for details. Please understand that the integrity policy also applies to the use of clickers. In particular, use of any clicker by someone other than a person to whom it is registered is a violation of the policy and will result in academic sanctions that could go well beyond the total value of all clicker-related assignments, depending on the severity of the violation. Basically, to avoid problems, you should never bring any clicker to class that is not your own.

CODE OF MUTUAL RESPECT
As the instructor for this course, I strongly endorse the Eberly College Code of Mutual Respect and Cooperation. I intend to adhere to these tenets in my dealings with students and I hope that students will reciprocate in their interations with all other students, teaching assistants, learning assistants, and me. The code may be found online at http://science.psu.edu/climate/code-of-mutual-respect-and-cooperation/Code-of-Mutual-Respect%20final.pdf/view.

DISABILITY ACCOMMODATION STATEMENT
Penn State welcomes students with disabilities into the University's educational programs. The Student Disability Resources (SDR) website at http://equity.psu.edu/sdr/disability-coordinator provides contact information for every Penn State campus. At University Park, the SDR office is in 116 Boucke. In order to receive consideration for reasonable accommodations, you must contact SDR and provide documentation as explained in the guidelines at http://equity.psu.edu/sdr/guidelines.

COUNSELING AND PSYCHOLOGICAL SERVICES STATEMENT
Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional wellbeing. The university offers a variety of confidential services to help you through difficult times, provided by staff who welcome all students. At University Park, Counseling and Psychological Services at University Park (CAPS) may be reached at 814-863-0395 or on the web at http://studentaffairs.psu.edu/counseling/. For emergencies 24 hours a day, 7 days a week, call the Penn State Crisis Line at 877-229-6400 or contact the Crisis Text Line by texting LIONS to 741741.

EDUCATIONAL EQUITY/REPORT BIAS STATEMENT
Students who believe they have experienced or observed a hate crime, an act of intolerance, discrimination, or harassment that occurs at Penn State are urged to report this incident as outlined on the University's Report Bias webpage at http://equity.psu.edu/reportbias/.