Lectures:  TR 9:30  10:45 a.m.  112 SWKT 
Labs:  TR 12:00  1:50 p.m.  112 SWKT 
The home page for Public Policy 603 is http://goodliffe.byu.edu/603/. Check the home page often for announcements, corrections, instructions for assignments, syllabus, etc. You should also check your email regularly. I suggest that you exchange phone numbers and/or email addresses with other students in the class.
I will hold office hours on Mondays and Wednesdays 34 p.m. I am also available at most other times if you make arrangements with me. 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. (Suggested topics: playing the organ, practicing yoga, student evaluations, Choose to Give program, BYU tuition.)
This course explores the fundamental concepts of research design and empirical analysis, with a heavy emphasis on econometrics.
This course is designed to help you
We will emphasize application and interpretation over theory. Thus, in addition to the textbook, we will read articles that apply these methods to problems in public policy.
The course will be run primarily as a lecture. However, I actively encourage questions, interruptions, cries for help, protests of disbelief, etc. You will never be penalized for participatingeven when this takes the form of vague complaints like, "I've got no clue why we are doing this stuff!" I urgeindeed, I expectyou to take advantage of the chance to talk with me during office hours.
As a result of its recent accreditation experience (and increasing emphasis from the Department of Education to measure educational outcomes, e.g. NCLB), each program at BYU 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. To learn the expected student outcomes for the Public Policy Program go here.
The specific learning objectives that this course fulfills include:
This is the first course in the statistical methods sequence in the Public Policy Masters Program. This course assumes that you have taken an introductory statistics course (such as PlSc 200, Stat 221, or Econ 378). This course also assumes a basic understanding of high school mathematics and calculus (e.g. Math 112). Students who mastered the material in their prerequisite course will be at an advantage. This course is taught at the graduatelevel and demands not only an understanding of the material in the course prerequisites but also the intellectual maturity and dedication required to work through the required readings and assignments at an intense pace. This will likely be the most demanding course you have this semester.
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.
Weekly Assignments  30% 
Midterm Exam  15% 
Final Exam  30% 
Research Project  25% 
All assignments are due at the beginning of class. If you have some sort of emergency, you can also turn in your assignment to me electronically (via email), after which you will turn in a hard copy. 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. Since everyone has difficulties at one time or another, I will drop the lowest assignment for the semester. I suggest you save your dropped assignment for when you have a good excuse for missing.
To understand statistics, you must use statistics. To facilitate understanding, there will be weekly assignments that may include any or all of the following:
You may work together on these assignments (in groups of two or at most three), but you must write up your answers separately. I give much 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. Generally, weekly assignments will be distributed and due on Thursdays.
There is a midterm and final exam. These are both takehome 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 takehome exams. The final exam will cover material for the whole semester. The exams will be discarded at the end of the Winter 2012 semester.
Each student will write a paper on a topic of his or her 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. (Of course, one requirement is that you have the necessary data.) In your project, you will test a theory that uses a continuous dependent variable (roughly) and at least two independent variables. There will be two steps (e.g. gathering data, preliminary analysis) that will be part of weekly assignments.
I strongly recommend that you consult with me and the teaching assistant through all phases of your research. We will be able to help you select a feasible topic, find data, or comment on your statistical model.
Assignment 
Date Due 
Percentage 

Proposal 
September 8  part of Assignment 1 
Data Summary 
October 6  part of Assignment 5 
Outline 
October 27  10% 
Paper 
December 1  60% 
Presentation  December 6 or 8  30% 
Turn in a onepage, doublespaced proposal (standard font and margins) outlining the research question you plan to address, explains a potential causal connection linking an independent and dependent variable, offers at least 4 relevant citations, and discusses possible data sources to be used.
Turn in a onepage, doublespaced 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.
Turn in a combination of initial results displayed in tables and figures, including model diagnostics, along with some bullet points interpreting your results.
The paper's technical level may be higher than the presentation's. However, you should still explain what your statistical results mean in layman's terms. 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. The papers may be picked up in the Political Science office (745 SWKT) after they are graded. The papers will be discarded at the end of the Winter 2012 semester.
As a statistical analyst, it is very 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?
All students will present their research during the last week of class. The presentation's technical level should be geared toward a generic public servantyou will have to explain what your statistical results mean. There will be a strict time limit, and you should be prepared to answer questions from the class and instructor. Further suggestions on presentations generally can be found here.
I will award the higher of two grades:
To use #2, you must complete at least 9 of the 10 weekly assignments (Assignment 0 does not count) and the midterm exam. (Turning in a sheet of paper with your name on it is not completing the assignment.) This allows students who take longer to get the material to still do well in the class. However, if you do not work on the weekly assignments, you will not do well on the final exam or research project.
Putting these statements together, the university expects an average graduate student to work more than 9 hours a week in a 3 credithour course to achieve excellence. The work load in this course is heavy but manageable.
Students who have succeeded in this course have the following characteristics. They
On Tuesdays and Thursdays at noon, there will be a computer lab in 112 SWKT led by the Teaching Assistant.
In the labs you will learn how to do basic and advanced statistics in Stata. The Stock and Watson website has a helpful tutorial here as well: Stock and Watson Stata tutorial. You will also learn how to do statistics in a couple of other programs to increase flexibility and marketability for future work opportunities. Each week, the lab will cover the commands necessary to do the weekly assignments.
During the first week of class, the FHSS Research Support Center will hold Stata workshops. Attending one of the workshops will give you a good base to begin your work with Stata this semester. The times are locations are:
You may find it useful to purchase your own copy of Stata. If you do not purchase your own copy, you need to plan ahead to use the computers in SWKT. Since some data sets we use have more than 1000 observations, you will need to purchase Stata/IC or Stata/SE.
I expect all students to have a working knowledge of the Windows operating system (i.e., what backslashes mean, how to use a mouse, how to use pulldown menus, etc.). If you do not have such knowledge, take some time to get familiar as soon as possible. It will not only benefit you in this class, but other classes and jobs. Of course, if you are already familiar with spreadsheets and statistical programs, this will also help you.
Please arrive in the Computer Lab before class starts to sign in and have everything ready to go when class starts.
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' (The Aims of a BYU Education, p. 6). 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 (parts attached to the original paper syllabus).
A colleague (Mitch Sanders, former professor at Notre Dame) has already explicated these issues specifically for political science. Please read here (also attached to the original paper syllabus).
If you write a paper for another course (past or present) that uses the same topic as a paper for this course, you need to approve it with me first, and then you must turn in to me a copy of the paper from your other course.
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 [PPol 603], 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."
"Discussion among students to understand the homework problems or to prepare for [exams] is encouraged."
"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. Wordbyword 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 BYU students, who have committed to the Honor Code, 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:
Title IX of the Education Amendments of 1972 prohibits sex discrimination against any participant in an educational program or activity that receives federal funds. The act is intended to eliminate sex discrimination in education. Title IX covers discrimination in programs, admissions, activities, and student to student sexual harassment. BYU's policy against sexual harassment extends not only to employees of the university but to students as well. If you encounter unlawful sexual harassment or gender based discrimination, please talk to your professor; contact the Equal Employment Office at 4225895 or 3675689 (24 hours); or contact the Honor Code Office at 4222847.
Brigham Young University is committed to providing a working and learning atmosphere which reasonably accommodates qualified persons with disabilities. If you have any disability which may impair your ability to complete this course successfully, please contact the University Accessibility Center (2170 WSC, 4222767). Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with the student and instructor by the SSD office. If you need assistance or if you feel you have been unlawfully discriminated against on the basis of disability, you may seek resolution through established grievance policy and procedures. You should contact the Equal Employment Office at 4225895, D282 ASB.
All readings should be read before class for full understanding of the subject material.
The text for the course is:
Do not buy the first edition of the book. There are significant improvements from the first to the second edition, including a new arrangement of chapters, and more problems and data sets to be used. (The third edition would probably be fine.) The book has a web site where you can download data sets and replication files here: Stock and Watson Student Resources.
The text is available at the BYU bookstore, or any number of online bookstores (see BooksPrice.com for a listing of bookstores and comparison of prices).
There may be other articles/chapters we will read that are available through links below:
Here are slides from past lectures:
Other information:
We will cover about a chapter a week.
Note: SW = Stock and Watson; AF = Agresti and Finlay
Date 
Topic 
Readings 
Assignments 

August 30 
Introduction  SW:1; AF:2.12.3 

September 1 
Probability  SW:2.12.3, AF:3.13.4  Assignment 0 Due 
6 
Sampling Distirbution  SW:2.42.6  
8 
Sampling Distribution  AF:4.14.6  Assignment 1 Due 
13 
Statistics  SW:3  
15 
Statistics  SW:13.113.2  Assignment 2 Due 
20 
Simple Regression  SW:4.14.3  
22 
Simple Regression  SW:4.44.6  Assignment 3 Due 
27 
Simple Regression  SW:5.15.3 

29 
Simple Regression  SW:5.45.7  Assignment 4 Due 
October 4 
Multiple Regression  SW:6.16.4  
6 
Multiple Regression  SW:6.56.8  Assignment 5 Due Project Data Summary 
11 
Multiple Regression  SW:7.17.4  
13 
Multiple Regression  SW:7.57.7,13.313.4  Assignment 6 Due 
18 
No class: Work on Midterm 


20 
Functional Forms  SW:8.18.2  Midterm Due 
25 
No class: Project Consultations 


27 
Interactions  SW:8.38.4  Project Outline 
November 1 
Interactions  SW:8.5  
3 
Validity  SW:9  Assignment 7 Due 
8 
Panel Data  SW:10.110.3  
10 
Time SeriesCross Section Data  SW:10.410.5  Assignment 8 Due 
15 
Time SeriesCross Section Data  SW:10.610.7,13.5.1  
17 
Binary Dependent Variables  SW:11.111.2  Assignment 9 Due 
22 
No class: Friday Instruction  
24 
No class: Thanksgiving  
29 
Binary Dependent Variables  SW:11.311.4  
December 1 
Binary Dependent Variables  SW:11.5  Research Project Due 
6 
Presentations  
8 
Presentations  Assignment 10 Due 

15 
Final Due 
I often use video clips from popular culture (television programs, movies) to illustrate and emphasize the readings.
I consulted numerous syllabi in designing this course. Particularly helpful were syllabi by Mike Findley, Jeremy Pope, Adam Glynn, Simon Jackman, Andrew Martin, and James Stock.
Public Policy 603 home page
Jay Goodliffe's home page
This page is http://goodliffe.byu.edu/603/syllabus.htm