Political Science 328
Quantitative Political Methodology

Course Syllabus
Fall 2008

Lecture: TR 3:00 - 4:15 p.m. B190 JFSB
Computer Labs: F 1:00 - 1:50 p.m. 102 or 112 SWKT
  F 2:00 - 2:50 p.m. 102 or 112 SWKT
  F 3:00 - 3:50 p.m. 102 SWKT

Instructor: Jay Goodliffe
Office: 752 SWKT
Office Hours: TR 10 - 11 a.m., and by appointment
Phone: 422-9136
e-mail: goodliffe@byu.edu

Teaching Assistants:
Greg Skidmore gskidman@gmail.com T 10, W 9: 381 SWKT
Bethany Howard-Meiners bethany.a.howard@gmail.com W 10, W 12: 381 SWKT
Philip Erickson cuke85@hotmail.com T 1, W 1: 381 SWKT
Grady Killian Deakin gradybabe@gmail.com T 2, W 3: 381 SWKT
Ashley Burton ashbashbur@gmail.com M 2, W 2: 381 SWKT

TA Office Hours:
Monday: 2
Tuesday: 10,1,2
Wednesday: 9,10,12,1,2,3

Contents:

Home Page
Office Hours
Objectives
Prerequisites
Requirements
How to Succeed in this Course
Readings
Computer Labs
Academic Honesty and Plagiarism
Discrimination
Schedule


Home Page

The home page for Political Science 328 is http://goodliffe.byu.edu/328/. Check the home page often for announcements, corrections, instructions for assignments, syllabus, etc. You should also check your email regularly.


Office Hours

I will hold office hours on Tuesdays and Thursdays 10-11 a.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, lifting weights, student evaluations, Choose to Give program, BYU tuition.)


Objectives

This course explores the fundamental concepts of empirical analysis in political science, with a heavy emphasis on econometrics. This course also fulfills the General Education Languages of Learning requirement.

This course is designed to help you

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 the Teaching Assistants and 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 programs in this department go here. The College welcomes feedback on the expected student learning outcomes. Any comments or suggestions you have can be sent to FHSS@byu.edu.


Prerequisites

PlSc 200 is a prerequisite for this course. PlSc 200 teaches basic statistical concepts, as well as writing and research techniques. This course builds on those concepts and assumes you know those techniques; without the prerequisite, it will be (more) difficult to succeed in this course. If you have not taken PlSc 200, take this course after you have. (And no, you should not try concurrent enrollment.)


Requirements

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

40%

Midterm Exam

15%

Final Exam

25%

Research Project

20%

All assignments are due at the beginning of class. Assignments must be typed and usually separated into four different packets, as directed on the assignment. 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 two lowest assignments for the semester. I suggest you save your dropped assignments for when you have a good excuse for missing.

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 Fridays.

Exams

There is a midterm and final exam. These are both take-home exams. They will require you to solve problems similar to those 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 2009 semester.

Research Project

Each student will write part of 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) or a binary dependent variable, and at least two independent variables. There will be a number of preliminary steps (e.g. gathering data, preliminary analysis) that will be part of weekly assignments.

For the project, students will produce the "research results" section of a paper. That is, you present the results of an analysis, along with an interpretation of those results. (You should not turn in the introduction, literature review, or conclusion.) Besides some prose, the write-up should contain tables and figures.

The paper's technical level should be geared toward a generic public servant--you will have to explain what your statistical results mean. In grading the paper, we 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, and the usual grammatical and spelling concerns. The papers will be discarded at the end of the Winter 2009 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?

I strongly recommend that you consult with me and the teaching assistants 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.


How to Succeed in this Course

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

I will award the higher of two grades:

  1. your overall point total
  2. your point total using only the final exam and research project

To use #2, you must turn in at least 9 of the 11 weekly assignments (Assignment 0 does not count) and the midterm exam. This allows students who take longer to get the material to still do well in the class. However, if you do not do the weekly assignments, you will not do well on the final exam or research project.

I include the following information from the BYU 2008-2009 Undergraduate Catalog, which guides how I grade and determine workload:

"The grade given in a course is the teacher's evaluation of the student's performance, achievement, and understanding in that subject as covered in the class. The following adjectives indicate the meaning of the letter grades:
A Excellent
B Good
C Satisfactory
D Minimum passing
E Unacceptable
"Hence, the grade A means that the student's performance, achievement, and understanding were excellent in the portion of the subject covered in the class.
"There are prerequisites that qualify students to be admitted to the more advanced classes offered by a department. A senior has added experience, understanding, and preparation and, consequently, progresses in courses that would have been impossible when the student was a freshman. The level of performance, achievement, and understanding required to qualify for each grade that carries credit (any grade other than E, UW, I, IE, or WE) is higher in a more advanced class than in those classes that precede it, and the student is prepared to work at this higher level" (p. 59).
"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" (p. 57).

Putting these statements together, the university expects an "average student" to work "much more" than 12 hours a week to receive an 'A' (= "excellence") in a 4 credit-hour course. This is my expectation as well.

This workload has been affirmed by President Bateman in his devotional addresses. On 7 September 1999, he stated, "It takes approximately three hours of study outside class for every hour in the classroom. If you take 15 hours of credit, you should allocate upward of 45 hours for study per week." On 19 September 2000, he advised, "Study daily--at least three hours for every hour in class."

Students who have succeeded in this course have the following characteristics. They


Readings

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 book has a web site where you can download data sets and replication files here: Stock and Watson Student Resources. There is also one recommended text:

The recommended text covers much of the same material (though with different emphases). Repeated exposure to the same material increases understanding. It also shows how to use Stata (see below). In addition, the last chapter has helpful suggestions for carrying out your research project. There are also some web sites that I can recommend which cover the material in the class.

These texts are available at the BYU bookstore, or any number of on-line bookstores (see BooksPrice.com for a listing of bookstores and comparison of prices).

There may be other readings available through links I will provide or through photocopies in the Department of Political Science office (745 SWKT).


Computer Labs

On Friday afternoon, there will be five computer labs in 102 SWKT (first lab on the left in the FHSS Computer Center) and 112 SWKT (fishbowl at the back). There are two labs each at 1 p.m. and 2 p.m., and one lab at 3 p.m., and are assigned according to registration. These labs are led by the Teaching Assistants.

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 may 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.

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 pull-down 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.


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 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 [PlSc 328], 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.
  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.
  7. VERBATIM COPYING OF ANY MATERIAL WHICH YOU SUBMIT FOR CREDIT WITHOUT REFERENCE TO THE SOURCE IS CONSIDERED TO BE ACADEMICALLY DISHONEST."


Discrimination

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.


Schedule (subject to change)

We will cover about a chapter a week.

Note: SW=Stock and Watson; P=Pollock.

Date

Topic

Readings

Assignments

September 2

Introduction SW:1, 2.1-2.2; P:GS

 

4

Sampling Distribution SW:2.3-2.6; P:1  

9

Statistics SW:3.1-3.4; P:2-4  

11

Statistics SW:3.5-3.7; P:5-7  

16

Simple Regression SW:4.1-4.3; P:8

 

18

Simple Regression SW:4.4-4.6

 

23

Simple Regression SW:5.1-5.4; P:9

 

25

Simple Regression SW:5.5-5.7

 

30

Multiple Regression SW:6.1-6.5  

October 2

Multiple Regression SW:6.6-6.8  

7

Multiple Regression SW:7.1-7.4  

9

Multiple Regression SW:7.5-7.7

 

14

Review  

 

16

Review

 

Midterm Distributed

21

Functional Forms SW:8.1-8.2; P:9  

23

Interactions SW:8.3-8.5 Midterm Due

28

Binary Dependent Variables SW:11.1-11.3; P:10  

30

Binary Dependent Variables SW:11.4-11.5  

November 4

Binary Dependent Variables    

6

Binary Dependent Variables    

11

Panel Data SW:10.1-10.3  

13

Time Series-Cross Section Data SW:10.4-10.7  

18

Instrumental Variables SW:12.1-12.3  

20

Instrumental Variables SW:12.4-12.6

 

25 No class--Friday Instruction    
27 No class--Thanksgiving    

December 2

Program Evaluation SW:13.1-13.4  

4

Program Evaluation SW:13.5-13.8  

9

Validity SW:9.1-9.5 Research Project Due

11

Review   Final Distributed

12-13

(Reading Days)    

18

    Final Due

Political Science 328 home page


Jay Goodliffe's home page


This page is http://goodliffe.byu.edu/328/syllabus.htm