General information that you may need at the beginning of the semester.
|Office Location:||426 Eggers|
|Office Hours:||Mon and Wed, 10:00-11:30, or by appointment.|
|Email Address:||wilcoxen at syr.edu|
Most course materials, including instructions for assignments and the corresponding due dates, will be posted at the main URL below. In addition, GitHub will be used for exchanging source code, and Blackboard will be used for submitting memos and presentations.
This is a project-oriented course focused on developing the skills needed analyze public policy issues that involve complex data or numerical analysis. Specific skills include: (1) assembling large, complex sets of data from multiple, heterogenous sources; (2) detecting and addressing errors and inconsistencies in the data; (3) examining that data with visualization and statistical tools; (4) characterizing the degree of uncertainty in conclusions drawn from the data, including the use of monte carlo methods; (5) communicating findings clearly and concisely in presentations and technical memos; and (6) creating public goods in the process by doing each step in a clear, well-documented way that emphasizes reproducibility by others. Most sessions will be highly interactive and include in-class exercises using the material being discussed.
There are two formal prerequisites: PAI 721 Introduction to Statistics and PAI 723 Economics for Public Decisions. In addition, PAI 724 Data-Driven Decision Making would usually be taken before this course.
Presentations and memo: 60% of final grade. The largest share of the grade will be three in-depth assignments that culminate in presentations or a memo. The first presentation will be a group project and the memo and second presentation will be individual assigments. The due dates of the presentations and memo are listed below.
Short projects: 25% of final grade. There will be several short projects during the semester. You may do the projects individually, or in small groups of up to three students. The projects will be graded both on accuracy and clarity of coding.
Exercises during class: 15% of final grade. Most classes will involve short in-class assignments that will help you practice the topics being discussed. They will be graded mostly on effort. An honest effort that’s on the right track but not exactly right will receive a check; a particularly good effort that’s mostly or entirely right will receive a check plus; and an effort that’s pretty far off track will receive a check minus. Any sort of check is significantly better than failing to turn in an assignment.
As you'll learn very quickly if you don't know it already, working with large, complex data sets using sophisticated analytical tools is a highly collaborative activity. Learning when and how to look for help will be part of the course. With that said, it will be important in some circumstances to document the line between your work and that of others. Here are some guidelines:
Syracuse University’s Academic Integrity Policy, found at the URL below, reflects the high value that we, as a university community, place on honesty in academic work. The policy defines our expectations for academic honesty and holds students accountable for the integrity of all work they submit. Students should understand that it is their responsibility to learn about course-specific expectations, as well as about university-wide academic integrity expectations. The policy governs appropriate citation and use of sources, the integrity of work submitted in exams and assignments, and the veracity of signatures on attendance sheets and other verification of participation in class activities. The policy also prohibits students from submitting the same work in more than one class without receiving written authorization in advance from both instructors. Under the policy, students found in violation are subject to grade sanctions determined by the course instructor and non-grade sanctions determined by the School or College where the course is offered as described in the Violation and Sanction Classification Rubric. SU students are required to read an online summary of the University’s academic integrity expectations and provide an electronic signature agreeing to abide by them twice a year during pre-term check-in on MySlice.
If you need accommodations for a disability, please contact the Office of Disability Services (ODS), visit the ODS website below, or visit the ODS office in Room 309 of 804 University Avenue, or call (315) 443-4498 or TDD: (315) 443-1371 for an appointment to discuss your needs and the process for requesting accommodations. ODS is responsible for coordinating disability-related accommodations and will issue students with documented Disabilities Accommodation Authorization Letters, as appropriate. Since accommodations may require early planning and generally are not provided retroactively, please contact ODS as soon as possible.
SU religious observances notification and policy, found at the URL below, recognizes the diversity of faiths represented among the campus community and protects the rights of students, faculty, and staff to observe religious holidays according to their tradition. Under the policy, students are provided an opportunity to make up any examination, study, or work requirements that may be missed due to a religious observance provided they notify their instructors before the end of the second week of classes for regular session classes and by the submission deadline for flexibly formatted classes. If you prefer, however, you can notify me directly by email. In either case, just check with me and we'll work out an arrangement that fits your schedule.