Political Science 328
Advanced Methods of Political Analysis
Course Syllabus
Fall 1998
MWF 9:00-9:50 a.m. in 793 SWKT
Instructor: Jay Goodliffe
Office: 752 SWKT
Phone: 378-9136
e-mail: goodliffe@byu.edu

Contents:

Office Hours
Objectives
Prerequisites
Approach
Requirements
Readings
Computer Classes
Class Time
Schedule


Office Hours

I will hold office hours on Monday and Wednesday afternoons 2:00-4:00. I am also available at most other times if you make arrangements with me. I encourage you to come by for any reason whatsoever.


Objectives

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


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. Please see me if you have not already had PlSc 200.


Approach

Given the small class size, this will not be a rigidly structured course. I welcome your input in determining what subjects we discuss, and how and when we cover it. There are some topics that we must cover, but others are flexible.

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.


Requirements

Weekly Assignments

25%

Review Essays on Herrnstein/Murray and Gould

15%

Midterm Exam

10%

Final Exam

20%

Research Project

25%

Class Participation

5%

All assignments are due at the beginning of class on the day designated in the course schedule. If you cannot make it to class, please leave the assignment in my box (in the Political Science office--745 SWKT) before class begins. I will deduct 20 points per day (including weekends) for late assignments (on a 100 point scale). That said, I am a reasonable person; 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, but you must write up your answers separately. If you do not learn how to analyze or solve problems on your own, you will have difficulty on the exams, review essays and research project.

Review Essays

We will read the Gould and Herrnstein/Murray books (see below) to examine how statistics can be applied in social science arguments. There is a review essay on the Herrnstein/Murray book due before the midterm exam. This is worth 7% of your grade. The book has received a lot of attention and criticism. Your job is not to review the book's potentially incendiary argument(s), but to review the book on its (statistical) merits and whether the statistics support those arguments.

There is another review essay on both books due near the end of the semester. This is worth 8% of your grade. In this essay, you need to examine both books' arguments, and how they relate to each other. As in the first essay, you will be graded on your ability to distill the authors' arguments, and to analyze statistical and logical strengths and weaknesses of those arguments.

Work on the review essays on your own.

Exams

There is a midterm and final exam. These are both take-home exams that you will have one week to finish. 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 (except the instructor). The final exam will cover material for the whole 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 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.

Proposal

5%

Outline

10%

Preliminary Analysis

10%

Presentation

25%

Paper

50%

Proposal

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

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 a list of sources whose work you build on. Also list where you have obtained your data.

Preliminary Analysis

Turn in a (no longer than) four-page paper that gives a more detailed outline of your paper. This should also include a detailed description of your statistical model (including what variables you use) and some relevant descriptive statistics for your data.

Presentation

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.

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.


Readings

There are three required books that are available for purchase at the bookstore:

The Gould and Herrnstein/Murray books are discussed above. The Gujarati book is an excellent statistics textbook that we will use throughout the course. I have placed the Gould and Herrnstein/Murray books on reserve at the Lee Library. (The library does not have Gujarati.)

There are three additional statistical books on reserve at the library. I would be happy to recommend other texts if you find these inadequate.

Although the title may discourage the serious reader, the Gonick & Smith book is an excellent introduction to statistics, particularly for those who find statistics dull and opaque. It also has the distinct advantage of being correct, even in the details (which is not always the case with such books). The Kennedy book has a different approach than most statistics texts: in each chapter it discusses a set of concepts qualitatively, then the same concepts quantitatively, and finally discusses the minutiae of those concepts. (There is a 3rd edition published in 1992, but the library does not have it.) The Kranzler and Moursund book is somewhere between Gujarati and Gonick & Smith.

There will be other readings available to photocopy in the Department of Political Science office (745 SWKT) mailboxes in a box marked "PlSc 328 Readings." All readings should be read before class for full understanding of the subject material.


Computer Classes

Some of our classes will be spent in the FHSS Computer Lab on the 11th floor. We will learn how to do basic statistics in a spreadsheet program, and how to do basic and advanced statistics in SPSS. 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 with as soon as possible. It will not only benefit you in this class, but all others. Of course, if you are already familiar with spreadsheets and statistical programs, this will also help you.

Please arrive in the Computer Lab (1145 SWKT) before class starts in order to start up the computer and have everything ready to go when class starts.


Class Time

Class starts at 9:00 a.m. I realize that this is early. The situation is aggravated by the fact that the Kimball Tower elevators are notoriously unreliable and slow. Count on taking 10 minutes to get to class once you have entered the lobby, and plan accordingly. Please arrive on time to class so that we may end on time.


Schedule (subject to change)

Date

Topic

Readings

Assignments

August 31

Introduction and Overview

 

 

September 2

Measures of Central Tendency

DG 1-3

 

4

No Class

 

Computer Familiarization

7

Holiday--No Class

 

 

9

Measures of Spread

 

 

11

Probabilities and Sampling

 

 

14

Quantitative Inference

DG 4

 

16

Regression Analysis

DG 5

 

18

Computer Class

 

 

21

Regression Analysis (continued)

 

 

23

Regression Analysis (continued)

 

Project Proposal Due

25

Computer Class

 

 

28

Assumptions of OLS

DG 6.1-6.5

 

30

Assumptions of OLS (continued)

 

 

October 2

Computer Class

 

 

5

Coefficient of Determination

DG 6.6-6.11

 

7

Regression Applications

DG 7

Project Outline Due

9

Computer Class

 

 

12

Functional Forms

DG 8

 

14

Dummy Independent Variables

DG 9

Review Essay #1 Due

16

Computer Class

 

 

19

Dummy Dependent Variables

DG 14.4-14.5

Midterm Exam Distributed

21

Dummy Dependent Variables (continued)

 

 

23

Computer Class

 

 

26

Multicollinearity

DG 10

Midterm Exam Due

28

Heteroscedasticity

DG 11

 

30

Computer Class

 

 

November 2

Autocorrelation

DG 12

 

4

Model Specification

DG 13

 

6

Computer Class

 

 

9

Simultaneous Equations

 

 

11

Simultaneous Equations (continued)

 

Project Preliminary Analysis Due

13

Computer Class

 

 

16

Maximum Likelihood

 

 

18

Indeterminacy and Selection Bias

 

 

20

Measurement Error

 

Review Essay #2 Due

23

Endogeneity

 

 

25

Holiday--No Class

 

 

27

Holiday--No Class

 

 

30

Process Tracing

 

 

December 2

Project Presentations

 

 

4

Project Presentations

 

 

7

Project Presentations

 

 

9

Project Presentations

 

 

NOTE! 10

Project Presentations

 

Final Exam Distributed

14

 

 

Project Paper Due

17

 

 

Final Exam Due


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