Syllabus -- PS 602
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Office: |
Class: | |
| Bob.Duval@mail.wvu.edu |
301A Woodburn |
G15 Woodburn |
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Phone: 293-3811 x5299 |
Hrs: MTWThF: 11:30-12:30 | Hrs: TTh 1:00-2:15 |
General
This course is designed to introduce the graduate student to the principle method of empirical inquiry in the social sciences - regression analysis. The overwhelming majority of studies which test hypotheses, empirically fit models, produce predictions, or estimate policy impacts are based upon some form of linear least squares analysis. This course will cover the range of these basic linear models. The level of mathematical treatment is somewhat more advanced than PS601, but will still be moderate. The course will not dwell upon derivations. We will discuss the mathematic treatment of the topics, but memorization of complex formulae and the ability to reproduce the mathematical treatment is not part of the course objectives. The conceptual understanding of the topics covered is, however, critical to succeeding in the class. While it is desirable to have had some prior coursework in regression analysis, this course begins with the basics.
The basic organizing concepts of the course are:
Course Requirements
The major course requirements are an in-class open-book examination
just after midsemester, a take-home final,
and a seminar paper due the next to last week of class. Each will
count 30%. The paper topic must be arranged with me, with
a preliminary outline/design approved by the 8th week of class. Need I
add that it must use regression analysis?
In addition, there will be a number of computer assignments. It is
expected that the student is at least moderately
familiar with a statistical package such as Stata, NCSS for Windows,
SPSS, or SAS, and as such, the teaching of
computer skills is not an objective of this course. The assignments are
for illustrative purposes, and in exchange
for not formally grading them, I expect you to complete them. Thus the
remaining 10% will be class participation/computer
exercises. I also ask that each person obtain some data of interest,
including at least one time series of at least
30 observations. This data may overlap with your paper, and may prove
useful during the course.
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Texts for the Course |
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| Basic Econometrics 4/e | Damodar N. Gujarati | McGraw-Hill (2003) Order |
| Regression Diagnostics | John Fox | Sage QASS #79 (1991) Order |
| Statistics with STATA (Suggested!) | Lawrence C. Hamilton | Thomson (2004) (Updated for Stata 9) Order |
A number of additional articles or books will be placed on an electronic reserve. In addition, I am beginning to assemble a methods bibliography that may prove useful for additional or supplemental material.
Course Notes
My class notes (the Powerpoint slides) are available to you. I recommend that you print about 12-18 slides ahead of the class lecture, rather than print the entire file at the beginning of the semester. [Instructions on saving paper when printing Powerpoint.] These slides will change as the course goes on. In fact, the best time to print them is about 5 minutes before class, since I will likely be revising them up until then!
- PS602Notes_Part1.ppt
- PS602Notes_Part2.ppt
- Model Specification
- Where to Next.ppt
Course Outline with Readings
This is an initial reading list. I will likely add a few more as the semester goes on.
| Week 1: Aug 21-23 | Introduction, Ordinary Least Squares |
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| Week 2: Aug 28- Aug 30 | Least Squares Estimation and Multiple Regression |
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| Week 3: Sept 4-6 | Assumptions of the Model: A closer look at the error terms |
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| Week 4: Sept 11-13 | Hypothesis Testing & Properties of Estimators |
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| Week 5: Sept 18-20 | Dummy Variables |
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| Week 6: Sept 25-27 | Multicollinearity |
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| Week 7: Oct 2-4 | Heteroskedasticity |
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| Week 8: Oct 9-11 | Autocorrelation and Trend: I |
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| Week 9: Oct 16-18 | Autocorrelation and Trend: II |
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| Week 10: Oct 23-25 | Model Specification and Stepwise Regression |
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| Week 11: Oct 30 - Nov 1 | Curvilinear and Non-Linear Regression |
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| Week 12: Nov 6-8 | Regression Diagnostics |
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| Week 13: Nov 13-15 | Dichotomous Dependent Variables - Logit & Probit (a quick look) |
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| Week 14: Nov 20-22 | Thanksgiving Recess |
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| Week 15: Nov 27- Nov 29 | Simultaneous Equations & Causal Modeling |
Papers Due Dec 4th !
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| Week 16 Dec 4-6 | Other Topics |
| Week 17 | Final Exam |
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