This course explores advanced topics in statistical analysis, building on basic linear regression learned in Political Science 300/328. This course is designed to help you:
This course relies on R, a free, open-source software that is widely used both in the social sciences and industry. Facility with a statistical software is essential to the practice of quantitative political science and to many careers into which our graduates move.
The BYU Department of Political Science has developed a set of expected student learning outcomes. These will help you understand the objectives of the curriculum in the program, including this class. In the parlance of the Political Science department's learning outcomes, this course helps you:
I regularly make announcements, clarifications, further instructions, etc., in class and by email and Learning Suite. You are responsible for all of these, even if you do not attend class. You are also responsible for keeping your email up to date at my.byu.edu. (You should let me know if your email changes during the semester.) I suggest that you exchange phone numbers and/or e-mail addresses with other students in the class.
I will hold office hours TBA. I am also available at other times if you make arrangements with me. My office hours will be held in my office on campus, 722 KMBL. There is also an option to meet via Zoom if you would prefer. I encourage you to come by to talk about assignments in the class, suggestions for improving the class, politics and current events, the perils of student life, or for any other reason.
Sam, your TA for this class, is a great resource. He has training in R and classes in Economics and Statistics that overlap with this class. He will also hold office hours to help with assignments and other course materials. I find that working with TAs is more productive if you come to the TAs with specific questions, having already worked on the problems. Here are some guidelines to make working with the TA more productive:Political Science 300/328 (or an equivalent class, such as Economics 388) is a prerequisite for this course. That course covered basic statistics, ordinary least squares and its pathologies, fixed effects models, and logit/probit models. If you have not taken POLI 300/328, you need to speak to me before proceeding. Students who mastered the material in their prerequisite course will be at an advantage.
Class will occur live and in person. There will likely some be lecture, some in-class exercises, and some time to work through problems and examples. Please be ready to start on the computers (i.e. logging in, etc.) when class begins.
We will emphasize application and interpretation over theory. Thus, in addition to the textbook, we will use articles that apply these methods to problems in political science and public policy.
A Chinese proverb (supposedly) says, "I hear and I forget, I see and I remember, I do and I understand." This philosophy drives the requirements of the class. The way you learn the material is to do statistical analysis. I choose problems and assignments to encourage this learning.
Weekly Assignments | 40% |
Midterm Exam | 15% |
Final Exam | 25% |
Research Project | 20% |
All assignments are due at the beginning of class, usually on Wednesdays. I will not accept late assignments. The primary reason for no late assignments is so that we can discuss the assignment in class immediately after it is turned in. If you anticipate a problem with submitting an assignment when it is due, speak to me before the assignment is due so that we can try to work out an alternative arrangement.
To understand statistics, you must use statistics. Each week you will be required to complete assignments that will include a variety of activities ranging from statistical theory problems to analyzing data and interpreting statistical results. Generally, weekly assignments will be posted on Learning Suite after class on Wednesday. (We will record scores on assignments and exams in Learning Suite as well.)
Except where explicitly directed otherwise, you may work together on these assignments (in groups of two or at most three), but you must write up your answers separately. That means you need to write up your code separately as well. I give more detailed instructions on how to report your work together in the Academic Honesty section below. Generally, if you use other persons' work, or make changes to your own work without inquiring or understanding what you did incorrectly, then you are trying to get a grade using someone else's knowledge. Giving or receiving answers in this manner is not permitted in this course. If you do not learn how to analyze or solve problems on your own, you will have difficulty on the exams and research project. As a regular practice, on each problem, state with whom you worked. If you worked alone, state that you worked alone.
There is a midterm and final exam. These are both take-home exams. They will require you to solve problems similar to case studies in the weekly assignments. You are not allowed to consult with anyone on these take-home exams. The exams are in place of the weekly assignment: There is no class during a take-home exam. The final exam will cover material for the whole semester.
Students will write and present a paper on a topic of their choosing. The project will allow you the opportunity to apply the skills that we will develop in this class to actual data and problems. You may pursue any topic of your choice, subject to instructor approval. (One requirement is that you have the necessary data.) There are a number of deadlines that must be met, noted on the course schedule.
I strongly recommend that you consult with me through all phases of your research. I may be able to help you select a feasible topic, find data, or comment on your statistical model. In their brief edition, Stock and Watson have a helpful chapter on "Conducting a Regression Study."
Assignment |
Date Due |
Percentage |
|---|---|---|
Proposal |
January 31 | part of Assignment 3 |
Data Summary |
February 28 | part of Assignment 6 |
| Poster | April 2 | 35% |
Paper |
April 10 | 65% |
Turn in a 1-2 page, double-spaced proposal (standard font and margins) outlining the research question you plan to address, explains a potential causal connection linking an independent and dependent variable, suggests which model(s) will be used, offers at least 4 relevant citations, and discusses possible data sources to be used. Discuss how this research is related to any other work you have done or are doing as a Research Assistant, or for a previous or concurrent class.
Turn in a one-page, double-spaced document (standard font and margins) that offers details about the data set that you have obtained. The summary should include summary statistics and any relevant figures that help describe the data. If you have changed your project, discuss how this research is related to any other work you have done or are doing as a Research Assistant, or for a previous or concurrent class.
You will present the poster at the Fulton Conference, details of which can be found here and here. (Other suggestions for posters are here.) You submit your poster here. The submission deadline is Tuesday, April 2, 2:00 p.m. The poster session takes place Thursday, April 11, 9:00 - 11:45 a.m. in Ballroom of the Wilkinson Student Center.
The paper's technical level may be higher than the poster. However, you should still explain what your statistical results mean in layperson's terms. You should provide an abstract. In grading the paper, I will consider how well you have used material from the course, how well you have used statistical analysis to test your hypotheses, if the analysis is actually correct (numerical accuracy and correct interpretation), how well you use charts and graphs, logic and organization of the paper, and the usual grammatical and spelling concerns. As a statistical analyst, it is important that you are aware of the limitations of your research. Under what circumstances do your results hold? Likewise, which circumstances would make them invalid? If you are unable to conduct the ideal analysis (perhaps due to resource constraints), explain what the proper approach would be. If you were able to use this superior approach, how would the results likely differ from the results you have?
The course is graded on a modified curve. The basic idea is that I will look for natural breaks between students and assign grades accordingly. Thus, I do not assign a set number or percentage of As and Bs.
I include the following information from the BYU University Policies, which guides how I grade and determine workload:
| A | Excellent |
| B | Good |
| C | Satisfactory |
| D | Minimum passing |
| E | Unacceptable |
Putting these statements together, the university expects an "average student" to work "much more" than 9 hours a week to receive an 'A' (= "excellence") in a 3 credit-hour course. This is my expectation as well.
As in many other subjects, learning to use data requires that you are exposed to it multiple times. Do not expect to understand everything in the book/video the first time you read/watch it. Do not expect to master the material after coming to a single lecture. It takes reading, hearing, and applying the material to grasp the concepts.
Students who have succeeded in this course have the following characteristics. They
From the Academic Honesty section of the BYU Honor Code: "The first injunction of the BYU Honor Code is the call to `be honest.' Students come to the university not only to improve their minds, gain knowledge, and develop skills that will assist them in their life's work, but also to build character. `President David O. McKay taught that character is the highest aim of education.' (See Aims of a BYU Education.) It is the purpose of the BYU Academic Honesty Policy to assist in fulfilling that aim."
"BYU students should seek to be totally honest in their dealings with others. They should complete their own work and be evaluated based upon that work. They should avoid academic dishonesty and misconduct in all its forms, including but not limited to plagiarism, fabrication or falsification, cheating, and other academic misconduct" (cite). Read the full version here.
A colleague (Mitch Sanders, former professor at Notre Dame) has already explicated these issues specifically for political science. Please read here.
In this class, you need to acknowledge the contributions of others toward your assignments. I have taken the following guidelines from MIT's Unified Engineering class. I have changed and added various words where appropriate:
"The fundamental principle of academic integrity is that you must fairly represent the source of the intellectual content of the work you submit for credit. In the context of [POLI 301], this means that if you consult other sources (such as fellow students, TA's, faculty, literature) in the process of completing homework [(or Stata codes)], you must acknowledge the sources in any way that reflects true ownership of the ideas and methods you used."
"Doing homework helps to engage with the concepts and material taught in class on a deeper level. To enhance the learning process we strongly suggest that you first try to solve the problems by yourself and then discuss challenges in groups or in office hours if necessary. Discussion among students and in office hours to digest the material and the homework problems or to prepare for [exams] is considered useful in the educational process. COLLABORATION ON HOMEWORK IS ALLOWED UNLESS OTHERWISE DIRECTED AS LONG AS ALL REFERENCES (BOTH LITERATURE AND PEOPLE) USED ARE NAMED CLEARLY AT THE END OF THE ASSIGNMENT. Word-by-word copies of someone else's solution or parts of a solution handed in for credit will be considered cheating unless there is a reference to the source for any part of the work which was copied verbatim. FAILURE TO CITE OTHER STUDENT'S CONTRIBUTION TO YOUR HOMEWORK SOLUTION WILL BE CONSIDERED CHEATING."
"Study groups are considered an educationally beneficial activity. However, at the end of each problem on which you collaborated with other students you must cite the students and the interaction. The purpose of this is to acknowledge their contribution to your work. Some examples follow:
Unfortunately, some students still profess ignorance of or attempt to find loopholes in the previous guidelines. As a result of sad experience, I repeat the following guidelines and add clarifications:
All reading should be read before class for full understanding of the subject material.
The text that we will refer to the most for the course is:
You can buy this book on
at the publisher's site
($50) or Amazon
($45). But you do not need to buy a physical copy of this book: A free version of the
entire book is available online here
("free to view and download for personal use only"). Besides being free, the online
version has the printing errors fixed. There will likely be other readings that I will
post on Learning Suite throughout the semester. Please check regularly to make sure that
you do not miss any.
We use the statistical program R extensively, and learning R is required for success
in this course. I will conduct classes on the assumption that you work using RStudio,
a front-end interface for R. It is freely available for any of the major operating
systems. You should download:
Brigham Young University prohibits all forms of sexual harassment—including sexual assault, dating violence, domestic violence, and stalking on the basis of sex—by its personnel and students and in all its education programs or activities. University policy requires all faculty members to promptly report incidents of sexual harassment that come to their attention in any way and encourages reports by students who experience or become aware of sexual harassment. Incidents should be reported to the Title IX Coordinator at t9coordinator@byu.edu or (801) 422-8692 or 1085 WSC. Reports may also be submitted online at https://titleix.byu.edu/report or 1-888-238-1062 (24-hours a day). BYU offers a number of resources and services for those affected by sexual harassment, including the university's confidential Sexual Assault Survivor Advocate. Additional information about sexual harassment, the university's Sexual Harassment Policy, reporting requirements, and resources can be found in the University Catalog, by visiting http://titleix.byu.edu, or by contacting the university's Title IX Coordinator.
Brigham Young University is committed to providing a working and learning atmosphere that reasonably accommodates qualified persons with disabilities. A disability is a physical or mental impairment that substantially limits one or more major life activities. Whether an impairment is substantially limiting depends on its nature and severity, its duration or expected duration, and its permanent or expected permanent or long-term impact. Examples include vision or hearing impairments, physical disabilities, chronic illnesses, emotional disorders (e.g., depression, anxiety), learning disorders, and attention disorders (e.g., ADHD). If you have a disability which impairs your ability to complete this course successfully, please contact the University Accessibility Center (UAC), 2170 WSC or 801-422-2767 to request a reasonable accommodation. The UAC can also assess students for learning, attention, and emotional concerns. If you feel you have been unlawfully discriminated against on the basis of disability, please contact the Equal Opportunity Office at 801-422-5895, eo_manager@byu.edu, or visit https://hrs.byu.edu/equal-opportunity for help.
Mental health concerns and stressful life events can affect students' academic performance and quality of life. BYU Counseling and Psychological Services (CAPS, 1500 WSC, 801-422-3035, caps.byu.edu) provides individual, couples, and group counseling, as well as stress management services. These services are confidential and are provided by the university at no cost for full-time students. For general information please visit https://caps.byu.edu; for more immediate concerns please visit http://help.byu.edu.
All course materials (e.g., outlines, handouts, syllabi, exams, quizzes, PowerPoint presentations, lectures, audio and video recordings, etc.) are proprietary. Students are prohibited from posting or selling any such course materials without the express written permission of the professor teaching this course. To do so is a violation of the Brigham Young University Honor Code. It is also unethical to post your own work (study sheets, papers) from the course on file sharing websites as you are encouraging others to engage in plagiarism. These policies continue indefinitely (not limited to the duration of the semester or term you take this course).
"Sadly, from time to time, we do hear reports of those who are at best insensitive and at worst insulting in their comments to and about others... We hear derogatory and sometimes even defamatory comments about those with different political, athletic, or ethnic views or experiences. Such behavior is completely out of place at BYU, and I enlist the aid of all to monitor carefully and, if necessary, correct any such that might occur here, however inadvertent or unintentional. "I worry particularly about demeaning comments made about the career or major choices of women or men either directly or about members of the BYU community generally. We must remember that personal agency is a fundamental principle and that none of us has the right or option to criticize the lawful choices of another." President Cecil O. Samuelson, Annual University Conference, August 24, 2010 "Occasionally, we ... hear reports that our female faculty feel disrespected, especially by students, for choosing to work at BYU, even though each one has been approved by the BYU Board of Trustees. Brothers and sisters, these things ought not to be. Not here. Not at a university that shares a constitution with the School of the Prophets." Vice President John S. Tanner, Annual University Conference, August 24, 2010
To facilitate productive and open discussions about sensitive topics about which there are differing opinions, members of the BYU community should: (1) Remember that we are each responsible for enabling a productive, respectful dialogue. (2)To enable time for everyone to speak, strive to be concise with your thoughts. (3) Respect all speakers by listening actively. (4) Treat others with the respect that you would like them to treat you with, regardless of your differences. (5) Do not interrupt others. (6) Always try to understand what is being said before you respond. (7) Ask for clarification instead of making assumptions. (8) When countering an idea, or making one initially, demonstrate that you are listening to what is being said by others. Try to validate other positions as you assert your own, which aids in dialogue, versus attack. (9) Under no circumstances should an argument continue out of the classroom when someone does not want it to. Extending these conversations beyond class can be productive, but we must agree to do so respectfully, ethically, and with attention to individuals' requests for confidentiality and discretion. (10) Remember that exposing yourself to different perspectives helps you to evaluate your own beliefs more clearly and learn new information. (11) Remember that just because you do not agree with a person's statements, it does not mean that you cannot get along with that person. (12) Speak with your professor privately if you feel that the classroom environment has become hostile, biased, or intimidating. Adapted from the Deliberation Guidelines published by The Center for Democratic Deliberation. (http://cdd.la.psu.edu/education/The%20CDD%20Deliberation%20Guidelines.pdf/view?searchterm=deliberation%20guidelines)
In the College of Family, Home, and Social Sciences, our classroom participation and behavior are guided by our mission statement, the BYU honor code, and principles of Christian discipleship. It is imperative that we value and respect every person as a child of Heavenly Parents who has divine worth. Consequently, we need to take steps to listen to, learn from, and love one another by striving to consider thoughtfully the opinions of others and use language that is polite, considerate, and courteous even when we strongly disagree. It is essential to create an educational environment that ensures "the gift of personal dignity for every child of God" (Holland). This includes embracing one another compassionately and "eliminating] any prejudice, including racism, sexism, and nationalism" (Ballard) "regardless of age, personal circumstances, gender, sexual orientation, or other unique challenges" (Nelson). It is vital to delight in individuality and welcome diverse perspectives and experiences as we "work tirelessly to build bridges of understanding rather than creating walls of segregation" (Nelson). To accomplish these goals we seek unity in higher principles of equity, charity, collaboration, and inclusiveness in order to build an environment in which all students, faculty, and staff can participate in, contribute to, and benefit equally from the academic community.
Some of this syllabus is based on the syllabus of Jeff Gill. Other syllabi consulted include BYU ECON 388, BYU ECON 398/488, BYU STAT 330.
Jay Goodliffe's home page
This page is http://goodliffe.byu.edu/428/syllabus.htm