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Course Site for Political Science 209 -- Fall 2018

Class resources for Political Science 209-905 & 209-906 Fall 2018

Instructor:

Professor Florian M. Hollenbach

Email: fhollenbach@tamu.edu; Web: fhollenbach.org

Office: 2061 Allen Building; Phone: 979-845-5021

Office Hours: Monday, Wednesday, & Friday: 10:40am - 11:45am or by appointment

Teaching Assistant:

Hwalmin Jin

Email: jymh33@tamu.edu

Office: 2050 Allen Building

Office Hours: Tuesday 1:30pm - 2:30 pm & Thursday 11:00am & 12:00pm (noon)

Class Meeting Time:

Monday, Wednesday, Friday:

Class Location: Bush Academic Building West (ALLN) __ 2003__ Unless otherwise noted or announced) Note this is a change from the original class location

Class Website:

All class materials, syllabus, notes, assignments will be posted on the class website: https://fhollenbach.github.io/Polisci209_2018

All assignments are to be submitted via eCampus, which is where I will also post your grades.

COURSE DESCRIPTION:

“I keep saying that the sexy job in the next 10 years will be statisticians, And I’m not kidding.”

Hal Varian, chief economist at Google

“Without data you’re just another person with an opinion.”

W. Edwards Deming

Data and data analysis are becoming more and more important for us as citizens in the modern nation state, the modern work place, and as consumers of increasingly complex information. At the same time, the understanding of statistical fundamentals is as pertinent as ever to read any political science research. This class serves two main purposes. First, it will help you understand the basic statistics that are necessary to read modern political science research. Second, you will gain an understanding of basic methods of data analysis and the underlying concepts of probability. We will also cover some introductory programming, so that you will be able to write code for basic statistical functions and plots in R.

LEARNING OUTCOMES:

At the end of the semester, after completing this course, students are expected to:

COURSE STRUCTURE & REQUIREMENTS:

The class will meet three times a week on Monday, Wednesday, and Friday. Classes will not simply be lecture based. We will cover programming, examples, and do in class exercises. This class will cover a variety of (complicated) concepts. Generally concepts will first be covered in the readings and we will go over specific applications and your questions on these concepts in class. It is therefore important for you to do you do the required reading and exercises listed under each date’s header before the respective class period. For most weeks, the readings & topics covered can be quite technical and challenging, which means it is even more important that you try to understand the material before coming to class. If you do not understand part of the readings, it is important to raise questions in class. That is the whole purpose of class time. I guarantee you will not be the only one that has trouble with the material and by asking questions, you are providing a service to your classmates. There will be regular homework and practice assignments. The assignments are for you to deepen your understanding of the material and study for the exam. Some of the assignments will be quite hard. It is, however, important for your own progress that you at least attempt to solve each problem on your own first, before seeking help. If you are stuck, I encourage you to seek help from your classmates first, then the TA or myself.

You are expected to do all readings prior to class, participate in class discussions, submit all assignments on time, and take quizzes and the final exam as scheduled.

GRADING & RESPONSIBILITIES:

Your grade will be based on one final exam (18%) at the end of the semester, two mid-semester quizzes (8% combined), class attendance (10%), participation, homework exercises (30% combined), and two longer writing assignments (34% combined). All assignments are to be submitted via eCampus before class on the day under which they are listed on the syllabus.

I expect you to do the assigned readings for each class before the lecture, participate in class discussions, and come prepared with questions. Specifically, you will be graded on:

The grading scale (in %) used in this class for all written assignments, exams, and the overall class grade will be the following:

Given that this course is an official writing course, you must pass the writing part of the class, i.e., the written assignments, to pass the class. As noted on the website of the Texas A&M Writing Center: “What happens if I don’t pass the W or C portion of a W or C course? If you complete a course with a passing grade but have not passed the W [..] portion of the course, you will not get the graduation credit for that W or C course.” (Link) This is not negotiable.

WRITING HELP:

The University Writing Center (UWC), located in 1.214 Sterling C. Evans Library and 205 West Campus Library, offers one-on-one consultations to writers. UWC consultations are highly recommended but are not required. Help is available with brainstorming, researching, drafting, documenting, revising, and more; no concern is too large or too small. UWC consultants will also help you improve your proofreading and editing skills. If you visit the UWC, take a copy of your writing assignment, a hard copy of your draft or any notes you may have, as well as any material you need help with. To find out more about UWC services or to schedule an appointment, call 458-1455, visit the web page at writingcenter.tamu.edu, or stop by in person.

ACADEMIC HONESTY:

All students should follow the highest standards of academic integrity. Cheating or plagiarism will not be tolerated in any way. If you are unsure what entails plagiarism, come talk to me. For more info, see: http://student-rules.tamu.edu/aggiecode & http://aggiehonor.tamu.edu. “An Aggie does not lie, cheat or steal, or tolerate those who do.” Your written assignments are to be submitted via Turnitin, which makes the detection of plagiarism and cheating very easy. Any cases of cheating or plagiarism will be submitted to the academic honor council, no exceptions.

Regarding group work: Unless explicitly otherwise specified, your homework and assignments are not to be done in groups and should be done alone. If you get stuck on a problem, you can discuss it in general terms with your fellow students, however, all solutions ought to be based your own work. Before asking for help from your fellow students, the TA, or myself, make sure you at least attempt to solve the problem yourself, otherwise you are only hindering your own learning.

READINGS & SOFTWARE:

We will primarily use Kosuke Imai’s “Quantitative Social Science”, which is available in the Texas A&M bookstore. You will need the hard copy of the book, otherwise it will be nearly impossible to pass the class. The book is comparatively affordable. If you truly can not afford to buy the book, come talk to me.

Required book: Imai, Kosuke. 2017. Quantitative Social Science: An Introduction. Princeton University Press. Princeton, NJ. ISBN: 978-0-691-16703-9.

You should have the book within the first week of class.

For part of this class we will be working on the computer with statistical software. We will use the statistical programming language R. R is available for download here:. I would recommend you download R-Studio, which is a software (a set of integrated tools) that makes the use of R much easier. You can download R-Studio here:. Both R and R-Studio are free. I would encourage you to install R-studio and play around with it for a bit.

You will also need a pocket calculator. You can buy a cheap one for at Walmart for about $3. Graphing calculators will not be allowed on the exams, so if you have any questions, please ask. Here is an example from Amazon for a calculator you could use. You should have your calculator by the Friday September 1st.

CLASSROOM BEHAVIOR, PARTICIPATION, & ELECTRONIC DEVICES:

We will usually meet three times a week during the semester. You can expect me to be prepared, give lecture, and answer questions. As outlined above, when you come to class, I expect you to be prepared as well and have the reading done before class. Remember, class is a resource to you. The exam and quizzes will be based on all lectures, readings, homework, and the discussions in class. Thus, only doing the required readings or only attending class will not be sufficient.

I strongly encourage you to not use a laptop in class, unless we are working together in R. Laptops have been shown to be a distraction not only to the students using them but also fellow class mates. A recent study has found that not having laptops in class can have a similar effect as hiring a SAT tutor

Laptops as distraction

If you think you have good reasons for why you need to use a computer, you may do so, but I ask those with laptops to sit in the back of the classroom.

In addition, please make sure your cell phones are on silent mode and refrain from using them during class time. If you are repeatedly on your phone, I may deduct points from your participation/attendance grade.

EXAM ABSENCES & LATE POLICY:

Make-up exam/quizzes will be permitted only in the case of university-excused absences. To be eligible for a make-up exam/quizzes, you will have to present original written documentation of legitimate circumstances that prevented you from taking the exam/quiz on time. Except in the case of observance of a religious holiday, to be excused, the student must notify his or her instructor in writing (acknowledged e-mail message is acceptable) prior to the date of absence. In cases where advance notification is not feasible (e.g. accident or emergency) the student must provide notification by the end of the second working day after the absence. This notification should include an explanation of why the notice could not be sent prior to the class. Accommodations sought for absences due to the observance of a religious holiday can be sought either prior or after the absence, but not later than two working days after the absence. Legitimate circumstances include religious holidays, illness (verified by a doctor), serious family emergencies and participation in group activities sponsored by the University, etc. See http://student-rules.tamu.edu/rule07 for additional information. Please note that I do not accept Xeroxed copies of medical excuses from students.

Unexcused absences from either exam will result in a score of 0 for the exam. Unexcused late work will be penalized by a 7.5 percentage point deduction for each day your work is late. For example, if you hand in the a writing assignment on the same day it is due, but after the stated deadline, your maximum score will be 92.5%. If you hand in your assignment more than 24hrs late, your maximum score will be 85%, after 48hrs it would be 77.5%, and so on. Late work will be excused only in the case of university-excused absences. Only under extreme circumstance will I make exceptions to these rules.

RE-GRADING POLICY:

Students that want to appeal a grade received on an exam or assignment must submit a regrading request in written form (e.g., email). This request has to be turned in within five working days after the graded exams or assignments are returned to the class. The written statement must explain exactly why the student believes the current grade is incorrect. I will then regrade the entire assignment or exam extra carefully. NOTE, as a consequence your grade may go up or down.

COMMUNICATION:

The best place to ask questions is in the classroom. If your question is not related to class material or relevant to other students, we can discuss it after class. I encourage you to visit my office hours to discuss any difficulties with the readings or homeworks. Again, however, you should at least attempt to solve the problem on your own first.

You can expect me to reply to emails within 24 hours during the work week. I will not reply to emails on the weekend, except for urgent matters. As with all business related correspondence, please include an appropriate salutation, identify yourself, and write in complete sentences.

DISABILITY:

All discussions will remain confidential. University policy is in accordance with the Americans with Disabilities Act Policy Statement. The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact Disability Services, currently located in the Disability Services building at the Student Services at White Creek complex on west campus or call 979-845-1637. For additional information, visit http://disability.tamu.edu.

Reasonable accommodations will be made for all students with disabilities, but it is the student’s responsibility to inform the instructor early in the term. Do not wait until just before an exam to decide you want to inform the instructor of a learning disability; any accommodations for disabilities must be arranged well in advance.

DIVERSITY POLICY:

The Department of Political Science supports the Texas A&M University commitment to diversity, and welcomes individuals from any racial, ethnic, religious, age, gender, sexual orientation, class, disability, and nationality. (See http://diversity.tamu.edu/. In the spirit of this vital commitment, in this course each voice in the classroom has something of value to contribute to all discussions.

Everyone is expected to respect the different experiences, beliefs and values expressed by fellow students and the instructor, and will engage in reasoned discussion that refrains from derogatory comments about other people, cultures, groups, or viewpoints.

Changes to Syllabus

I reserve the right to update/modify/clarify the syllabus with advance notification.

Class Schedule

Week 1

Monday, August 27th: What are we doing in this class?

Wednesday, August 29th: Installing and Introduction to R

Friday, August 31st: FASB PANEL – Meeting in 1015

Week 2

Monday, September 3rd: More introduction to R & Getting Everyone up to Speed

Wednesday, September 5th: Introduction to causality

Friday, September 7th: In Class Exercise on Causality

Week 3

Monday, September 10th: Continue Exercise on RCTs

Wednesday, September 12th: Review HW & Observational Studies

Friday, September 14th:

Week 4

Monday, September 17th: In Class Exercise on Observational Studies

Wednesday, September 19th: Introduction to Measurement – Meeting in 1015

Friday, September 21st: In Class Exercise on Measurement

Week 5

Monday, September 24th: Review HW & Univariate Data Summaries

Wednesday, September 26th: Bivariate Relationships – Meeting in 1015

Friday, September 28th: Starting with Writing Assignment 1

Week 6

Monday, October 1st: In Class Exercise Measurement & Bivariate Relationships

Wednesday, October 3rd: In Class Exercise Measurement & Bivariate Relationships

Friday, October 5th: Introduction to Prediction

Week 7

Monday, October 8th: Introduction to Prediction 2

Wednesday, October 10th: In Class Exercise Prediction

Friday, October 12th: Introduction to Regression

Week 8

Monday, October 15th: In Class Exercise Regression (or Catch up)

Wednesday, October 17th: Catch-Up Day & Regression Review

Friday, October 19th: In Class Exercise on Linear Regression

Week 9

Monday, October 22nd: Introduction to Probability

Wednesday, October 24th: Playing Cards

Friday, October 26th: Reviewing Probability 1

Week 10

Monday, October 29th: Conditional Probability

Wednesday, October 31st: In class Exercise on Probability

Friday, November 2nd: Starting with Writing Assigment 2

Week 11

Monday, November 5th: More Probability

Wednesday, November 7th: Reviewing Probability

Friday, November 9th: In Class Exercise on Election Fraud in Russia

Week 12

Monday, November 12th: Reviewing Homework + Introduction to Uncertainty

Wednesday, November 14th: Introduction to Uncertainty Continued

Friday, November 16th: In Class Exercises about Uncertainty

Week 13

Monday, November 19th: In Class Exercises on Uncertainty

Wednesday, November 21st:

Turkey Break!

Week 14

Monday, November 26th: In Class Exercise on Uncertainty

Wednesday, November 28th: Linear Regression with Uncertainty

Friday, November 30th: In class Exercise on Regression with Uncertainty

Week 15

Monday, December 3rd: Review of Uncertainty

Wednesday, December 5th

Friday, December 7th: Exam for 209-905 from 10:00 – 12:00 p.m. (noon)

Monday, December 10th: Exam for 209-906 from 8:00 – 10:00 a.m.