Public Policy 603
Data Analysis 1

Course Syllabus
Fall 2010

Lectures: TR 9:30 - 10:45 p.m. 105 SWKT
Labs: T 12:00 - 1:50 p.m. 105 SWKT
  R 4:00 - 4:50 p.m. 105 SWKT

Instructor: Jay Goodliffe
Office: 752 SWKT
Office Hours: TR 3-4 p.m., and by appointment
Phone: 422-9136
Teaching Assistant: Brenton Swenson
Office: TBA
Office Hours: TBA


Home Page
Office Hours
Learning Outcomes
How to Succeed in this Course
Computer Labs
Academic Honesty and Plagiarism

Home Page

The home page for Public Policy 603 is 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 e-mail addresses with other students in the class.

Office Hours

I will hold office hours on Tuesdays and Thursdays 3-4 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.)

Learning Outcomes

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

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 graduate-level 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.


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 participating--even when this takes the form of vague complaints like, "I've got no clue why we are doing this stuff!" I urge--indeed, I expect--you to take advantage of the chance to talk with me during office hours.


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


Midterm Exam


Final Exam


Research Project


All assignments are due at the beginning of class. You will most likely turn these in electronically to the TA. 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.

Weekly Assignments

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 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 final exam will cover material for the whole semester. The exams will be discarded at the end of the Winter 2011 semester.

Research Project

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. (Of course, 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 and the teaching assistant 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.



Outline and Bibliography




Final Paper



Turn in a (no longer than) one-page proposal outlining the research question you wish to address, and how you plan to address it. Discuss why the research question is interesting, and possible data sources.

Outline and Bibliography

Turn in a (no longer than) two-page outline of your paper sketching out the argument you plan to make and/or hypotheses you will test, and how you will do it. Include an annotated bibliography of sources whose work you build on. Also list where you have obtained your data.


All students will present their research during the last week or two of class. The presentation's technical level should be geared toward a generic public servant--you 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.

Final Paper

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 2011 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?

How to Succeed in this Course

The course is graded on a modified curve, using statistical principles that will be explained in the course.

"The expectation for undergraduate courses is three hours of work per week per credit hour for the average student who is appropriately prepared; much more time may be required to achieve excellence" (cite).

"Graduate study is more rigorous than undergraduate study" (cite).

Putting these statements together, the university expects an average graduate student to work more than 9 hours a week in a 3 credit-hour 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

Computer Classes

Mondays and Wednesdays after class will be spent in the FHSS Computer Lab on the 1st floor. We will learn how to implement the econometric tools in Stata and other statistical programs, such as SPSS, SAS, and Excel. This is to increase flexibility and marketability for future work opportunities. Each week, the labs will cover the commands necessary to do the weekly assignments, go over past assignments, and review the material generally. 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 pull-down menus, etc.).

Please arrive in the Computer Lab (105 SWKT) before class starts to start up the computer and have everything ready to go when class starts.

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.

Academic Honesty and Plagiarism

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. 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 Group Guidelines"

"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:

  1. You discuss concepts, approaches and methods that could be applied to a homework problem before either of you start your written solution. This process is encouraged. You are not required to make a written acknowledgment of this type of interaction.
  2. After working on a problem independently, you compare answers with another student, which confirms your solution. You should acknowledge that the other student's solution was used to check your own. No credit will be lost if the solutions are correct and the acknowledgments is made.
  3. After working on a problem independently, you compare answers with another student, which alerts you to an error in your own work. You should state at the end of the problem that you corrected your error on the basis of checking answers with the other student. No credit will be lost if the solution is correct and the acknowledgment is made, and no direct copying of the correct solution is involved.
  4. You and another student work through a problem together, exchanging ideas as the solution progresses. Each of you should state at the end of the problem that you worked jointly. No credit will be lost if the solutions are correct and the acknowledgment is made. [You must still write up your solutions individually, not jointly.]
  5. You copy all or part of a solution from a reference such as a textbook. You should cite the reference. Partial credit will be given, since there is some educational value in reading and understanding the solution. However, this practice is strongly discouraged, and should be used only when you are unable to solve the problem without assistance.
  6. You copy verbatim all or part of a solution from another student. This process is prohibited. You will receive no credit for verbatim copying from another student when you have not made any intellectual contribution to the work you are both submitting for credit.

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 422-5895 or 367-5689 (24 hours); or contact the Honor Code Office at 422-2847.

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, 422-2767). 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 422-5895, D-282 ASB.


All readings should be read before class for full understanding of the subject material.

There is two required books that are available for purchase at the BYU bookstore (see for a listing of bookstores and comparison of prices):

There is a website associated with examples from an earlier edition of the Wooldridge textbook here.

There are two additional statistical books that are recommended:

There are other articles we will read that are available through links below. These articles are examples of policy analyses using the tools we are learning:

Schedule (subject to change)

Note: W=Wooldridge; B=Baum; H=Hamilton; R=Research and Education Association





August 31

Introduction W:1; B:1; H:1


September 2

Sampling Distribution W:B,C.1-C.2; R:6-8 Assignment 0 Due


Statistics W:C.3-C.5; R:9  


Hypothesis Testing W:C.4-C.7; R:10; H:5

Assignment 1 Due


Simple Regression W:2.1-2.3; H:173-177



Simple Regression W:2.4-2.6

Assignment 2 Due


Multiple Regression: Estimation W:3; B:4.1-4.4; H:178-179 Proposal Due


Multiple Regression: Hypothesis Testing W:4; B:4.5; H:190-192

Assignment 3 Due


Multiple Regression: OLS W:5  


Functional Form W:6.1-6.2; H:236-243 Assignment 4 Due

October 5

Fit W:6.3-6.4; B:4.6-4.7; H:179-186 Outline Due


Dummy Variables W:7.1-7.3; B:7.1; H:192-199

Assignment 5 Due


Interactions W:7.4,7.6; B:7.2-7.4.1





Assignment 6 Due
Midterm Distributed


LPM and Probit W:7.5,17.1; B:10.1  


Logit W:17.1; H:10 Midterm Due


Limited Dependent Variables W:17.2-17.4; B:10.2-10.3  


Sample Selection W:17.5; B:10.4 Assignment 7 Due

November 2

Heteroskedasticity W:8; B:6.1-6.2  


Misspecification W:9.1-9.3; B:5.1-5.2; H:7 Assignment 8 Due


Missing Data W:9.4-9.6  


Time Series W:10.1-10.3; B:7.4.2 Assignment 9 Due


Time Series W:10.4-10.5; H:361-362  


Autocorrelation W:12.1-12.2; B:6.3 Assignment 10 Due


No class--Friday Instruction    


No class--Thanksgiving  


Autocorrelation W:12.3-12.6  

December 2

Review   Final Paper Due




Presentations   Assignment 11 Due
Final Distributed


(Reading Day)    


    Final Due

Public Policy 603 home page

Jay Goodliffe's home page

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