### Profile

# Tse-min Lin

### Associate Professor — Ph.D., University of Minnesota

#### Contact

- E-mail: tml@austin.utexas.edu
- Phone: 512-232-7248
- Office: BAT 4.144
- Campus Mail Code: A1800

### Biography

An Associate Professor at the Department of Government at the University of Texas at Austin, Professor Lin has taught or visited at State University of New York at Stony Brook, Duke University, Michigan State University, and the Institute of Political Science at Academia Sinica. His teaching and research interests cover methodology, formal theory, and American and comparative political behavior.

He has published in *American Journal of Political Science, American Political Science Review, Democratization, Journal of Democracy, Journal of Politics, Political Analysis, Political Research Quarterly, Public Choice, Social Science History, Taiwan Journal of Democracy, World Politics*, as well as in edited volumes. His recent work includes "The Dynamics of the Partisan Gender Gap" (*American Political Science Review*, Vol. 98, No. 3, August 2004), "Neighborhood Influence on the Formation of National Identity in Taiwan: Spatial Regression with Disjoint Neighborhoods" (*Political Research Quarterly*, Vol. 59, No. 1, March 2006), "Markets and Politics: The 2000 Taiwanese Presidential Election" (in Melvin Hinich and William A. Barnett, eds., *Topics in Analytical Political Economy*. Amsterdam: Elsevier, 2007), and “The Structure of Taiwan’s Political Cleavages toward the 2004 Presidential Election: A Spatial Analysis” (*Taiwan Journal of Democracy*, Vol. 4, No. 2, December 2008). Conference papers include “The Minimum-Sum Point as a Solution Concept in Spatial Voting,” “Spatial Regression, Increasing Returns, and Regionalism,” “The Spatial Organization of Elections and the Cube Law,” and “Modeling Rebellion Intensity with a Zero-Inflated Ordered Probit Model.”

### GOV 350K • Statistical Anly In Polit Sci

######
37744 •
Fall 2015

Meets
TTH 200pm-330pm BUR 136

show description
**Semester Fall 2015**

**GOV 350K – **Statistical Analysis in Political Science

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

37744 LIN

**Course Description**

This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.

Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.

**Prerequisites**

None

**Grading Policy**

Homework Assignments (6-7 sets): 30%

In-Class Midterm Exam: 30%

In-Class Final Exam: 30%

Instructor Discretion (Attendance, Participation, etc.): 10%

**Required Texts**

* T. H. Wonnacott and R. J. Wannacott. 1990. *Introductory Statistics*, 5th Ed. Wiley. (Or 4th Ed., *Introductory Statistics for Buisness and Economics*, 1990, which is the same as the 5th Ed.)

**Optional Texts**

* S. B. Green and N. J. Salkind, 2013. *Using SPSS for Windows and Macintosh: Analyzing and Understanding Data*, 7th Ed. Prentice Hall.

### GOV 385L • Advanced Statistical Analysis

######
37945 •
Fall 2015

Meets
TTH 500pm-630pm MEZ 1.204

show description
**Semester Fall 2015**

**GOV 385L – Title** Advanced Statistical Analysis

**SDS 385.14 – Title** Maximum Likelihood Estimation

Substantial Writing Component: NO

**Unique Days Time Bldg/Room Instructor**

37945 (56290) TTH 5:00-6:30p MEZ 1.204 LIN

**Course Description**

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.

**Prerequisites**

Statistical Analysis in Political Science II or its equivalent

**Grading Policy**

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

**Required Texts**:

* G. King.1998. *Political Methodology: The Likelihood Theory of Statistical Inference*.

Michigan.

* J. S. Long and J. Freese. 2014. *Regression Models for Categorical Dependent*

*Variables Using Stata*. 3nd ed. Stata Press.

**Recommended Texts:**

** **

* S. R. Eliason. 1993. *Maximum Likelihood Estimation: Logic and Practice.* Sage.

* W. H. Greene. 2012. *Econometric Analysis*. 7th ed. Pearson & Prentice Hall.

* T. F. Liao. 1994. *Interpreting Probability Models*. Sage.

* P. H. Pollock, III. 2010. A STATA Companion to Political Analysis. 2nd ed. CQ Press.

* A packet of journal articles and book chapters.

### GOV 350K • Statistical Anly In Polit Sci

######
37950 •
Spring 2015

Meets
TTH 1100am-1230pm BUR 112

show description
Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

37950 TTH 11:00am-12:30pm BUR 112 LIN

**Course Description**

This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.

Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.

**Prerequisites**

None

**Grading Policy**

Homework Assignments (6-7 sets): 30%

In-Class Midterm Exam: 30%

In-Class Final Exam: 30%

Instructor Discretion (Attendance, Participation, etc.): 10%

**Required Texts**

* T. H. Wonnacott and R. J. Wannacott. 1990. *Introductory Statistics*, 5th Ed. Wiley. (Or 4th Ed., *Introductory Statistics for Buisness and Economics*, 1990, which is the same as the 5th Ed.)

**Optional Texts**

* S. B. Green and N. J. Salkind, 2011. *Using SPSS for Windows and Macintosh: Analyzing and Understanding Data*, 6th Ed. Prentice Hall.

### GOV 355M • Human Behav As Rational Actn

######
37990 •
Spring 2015

Meets
TTH 330pm-500pm MEZ 1.216

show description

Writing Flag & Quantitative Reasoning Flag

** **

**Unique Days Time Bldg/Room Instructor**

37990 TTH 3:30-5:00pm MEZ 1.216 LIN

**Course Description**

The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.

In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “Free-Rider Problem” a contrast between rational man and irrational society. Self-serving behavior of individuals does not usually lead to collectively satisfactory results.

So this course is about the stories of the Prisoners, the Herdsmen, and the Free-Riders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story - a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.

**Prerequisites**

Upper-division standing required.

6 semester hours of lower-division coursework in government.

**Grading Policy**

1. First Paper (6-8 pages): 25% 2. Second Paper (7-9 pages): 25%

3. Third Paper (8-10 pages): 30% 4. Presentation: 10%

5. Attendance: 10%

**Texts**

1. Thomas C. Schelling (1978), *Micromotives and Macrobehavior* (Norton).

2. Robert Axelrod (1984), *The Evolution of Cooperation* (Basic Books).

3. Dennis Chong (1991), *Collective Action and the Civil Rights Movement* (Chicago).

4. Elinor Ostrom (1990), *Governing the Commons* (Cambridge).

5. Howard Rheingold (2002), *Smart Mobs: The Next Social Revolution *(Basic Books).

6. Clay Shirky (2009), *Here Comes Everybody* (Penguin Books).

### GOV 385L • Advanced Statistical Analysis

######
39080 •
Fall 2014

Meets
TTH 500pm-630pm MEZ 1.204

show description
**Semester Fall 2014**

**GOV 385L – Title** Advanced Statistical Analysis

Substantial Writing Component: NO

**Course Description**

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.

**Prerequisites**

Statistical Analysis in Political Science II or its equivalent

**Grading Policy**

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

**Required Texts**:

* S. R. Eliason. 1993. *Maximum Likelihood Estimation: Logic and Practice.* Sage.

* G. King.1998. *Political Methodology: The Likelihood Theory of Statistical Inference*.

Michigan.

* T. F. Liao. 1994. *Interpreting Probability Models*. Sage.

* A packet of journal articles and book chapters.

**Recommended Texts:**

** **

* W. H. Greene. 2012. *Econometric Analysis*. 7th ed. Pearson & Prentice Hall.

* J. S. Long and J. Freese. 2006. *Regression Models for Categorical Dependent*

*Variables Using Stata*. 2nd ed. Stata Press.

### GOV 385L • Time-Series Analysis

######
39082 •
Fall 2014

Meets
M 330pm-630pm GAR 1.134

show description
Writing Flag: NO

**Course Description**

This course is designed to examine the formal and statistical structure of techniques useful for analyzing dynamic processes. Subtopics include difference equations; stationary ARMA processes; persistent and/or nonstationary processes including integrated, fractionally integrated, and near-integrated processes; the estimation and forecasting of time series single equation regression; cointegration and error correction; Granger causality and vector autoregression; time-varying parameter regression, and time-series cross-section models.

**Prerequisites**

Statistical Analysis in Political Science II or its equivalent

**Grading Policy**

- Homework Assignments (20%)
- Project/Paper Proposal (20%)
- Final Project/Paper (60%)

**Required Texts**:

- Walter Enders. 2009.
*Applied Econometric Time Series*, 3e. Wiley. - Patrick T. Brandt and John T. Williams. 2007.
*Multiple Time Series*. Sage. - A packet of journal articles and book chapters.

**Recommended Texts**

- C. Chatfield. 1996.
*The Analysis of Time Series: An Introduction*, 5e. Chapman and Hall. - Samuel Goldberg. 2010.
*Introduction to Difference Equations: With Illustrative Examples from Economics, Psychology, and Sociology*. Dover. - John M. Gottman. 1981.
*Time-Series Analysis: A Comprehensive Introduction for Social Scientists*. Cambridge - Damodar N. Gujarati. 2003.
*Basic Econometrics*, 4e. McGraw-Hill & Irwin. - G. S. Maddala and In-Moo Kim. 1998. Unit Roots, Cointegration, and Structural Change. Cambridge.
- Richard McCleary and Richard A. Hay, Jr. 1980.
*Applied Time Series Analysis for the Social Sciences*. Sage. - Robert S. Pindyck and Daniel L. Rubinfeld. 1997.
*Econometric Models and Economic Forecasts*, 4e. McGraw-Hill.

### GOV 355M • Human Behav As Rational Actn

######
39210 •
Spring 2014

Meets
TTH 330pm-500pm MEZ 1.216

show description
**Course Description**

The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.

In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “Free-Rider Problem” a contrast between rational man and irrational society. Self-serving behavior of individuals does not usually lead to collectively satisfactory results.

So this course is about the stories of the Prisoners, the Herdsmen, and the Free-Riders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story - a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.

**Prerequisites**

Upper-division standing required.

6 semester hours of lower-division coursework in government.

**Grading Policy**

1. First Paper (6-8 pages): 25% 2. Second Paper (7-9 pages): 25%

3. Third Paper (8-10 pages): 30% 4. Presentation: 10%

5. Attendance: 10%

**Texts**

1. Thomas C. Schelling (1978), *Micromotives and Macrobehavior* (Norton).

2. Robert Axelrod (1984), *The Evolution of Cooperation* (Basic Books).

3. Dennis Chong (1991), *Collective Action and the Civil Rights Movement* (Chicago).

4. Elinor Ostrom (1990), *Governing the Commons* (Cambridge).

5. Howard Rheingold (2002), *Smart Mobs: The Next Social Revolution *(Basic Books).

6. Clay Shirky (2009), *Here Comes Everybody* (Penguin Books).

**FLAG:** Writing

### GOV 380R • Math Methods For Pol Analysis

######
39405 •
Spring 2014

Meets
TTH 1230pm-200pm BAT 1.104

show description
**Course Description**

This course introduces the mathematical concepts and methods essential for multivariate statistical analysis and formal political theory. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, constrained optimization, and difference and differential equations. Applications in multivariate statistical analysis include multiple regression, principal component analysis, factor analysis, etc., and their estimation in matrix form. Applications in formal political theory include equilibrium analysis, dynamic analysis, and spatial analysis.

**Course Requirements**

Statistical Analysis in Political Science I

**Grading Policy**

1. Homework Assignments: 40% 2. Final Project: 60%

**Texts**

1. Alpha C. Chiang and Kevin Wainwright. 2004. *Fundamental Methods of Mathematical Economics*, 4th ed. McGraw-Hill/Irwin.

2. J. Douglas Carroll and Paul E. Green. 1997. *Mathematical Tools for Applied Multivariate Analysis.* Revised ed. Academic Press.

3. (Optional) Jeff Gill. 2006. *Essential Mathematics for Political and Social Research*. Cambridge.

4. (Optional) Will H. Moore and David A. Siegel. 2013. A Mathematics Course for Political & Social Research. Princeton.

4. (Optional) John Fox. 2009. *A Mathematical Primer for Social Statistics*. Sage.

### GOV 350K • Statistical Anly In Polit Sci

######
39195 •
Fall 2013

Meets
MWF 100pm-200pm BUR 208

show description
**Prerequisites**

None

** **

**Course Description**

This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.

Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, and other statistical procedures. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.

**Grading Policy**

Homework Assignments (6-7 sets): 30%

In-Class Midterm Exam: 30%

In-Class Final Exam: 30%

Instructor Discretion (Attendance, Participation, etc.): 10%

**Required Texts**

* T. H. Wonnacott and R. J. Wannacott. 1990. *Introductory Statistics*, 5th Ed. Wiley. (Or 4th Ed., *Introductory Statistics for Buisness and Economics*, 1990, which is the same as the 5th Ed.)

**Optional Texts**

* S. B. Green and N. J. Salkind, 2011. *Using SPSS for Windows and Macintosh: Analyzing and Understanding Data*, 6th Ed. Prentice Hall.

### GOV 385L • Advanced Statistical Analysis

######
39390 •
Fall 2013

Meets
TTH 500pm-630pm MEZ 1.204

show description
**Prerequisites**

Statistical Analysis in Political Science II or its equivalent

**Course Description**

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis

**Grading Policy**

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

**Required Texts**

* S. R. Eliason. 1993. *Maximum Likelihood Estimation: Logic and Practice.* Sage.

* G. King.1998. *Political Methodology: The Likelihood Theory of Statistical Inference*.

Michigan.

* T. F. Liao. 1994. *Interpreting Probability Models*. Sage.

* A packet of journal articles and book chapters.

**Recommended Texts**

* W. H. Greene. 2012. *Econometric Analysis*. 7th ed. Pearson & Prentice Hall.

* J. S. Long and J. Freese. 2006. *Regression Models for Categorical Dependent*

*Variables Using Stata*. 2nd ed. Stata Press.

### GOV 355M • Human Behav As Rational Actn

######
38865 •
Spring 2013

Meets
TTH 200pm-330pm MEZ 1.216

show description
**Prerequisites**

Upper-division standing required.

6 semester hours of lower-division coursework in government.

**Course Description**

The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.

In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “Free-Rider Problem” a contrast between rational man and irrational society. Self-serving behavior of individuals does not usually lead to collectively satisfactory results.

So this course is about the stories of the Prisoners, the Herdsmen, and the Free-Riders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story - a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.

**Grading Policy**

1. First Paper (6-8 pages): 25% 2. Second Paper (7-9 pages): 25%

3. Third Paper (8-10 pages): 30% 4. Presentation: 10%

5. Attendance: 10%

**Texts**

1. Thomas C. Schelling (1978), *Micromotives and Macrobehavior* (Norton).

2. Robert Axelrod (1984), *The Evolution of Cooperation* (Basic Books).

3. Dennis Chong (1991), *Collective Action and the Civil Rights Movement* (Chicago).

4. Elinor Ostrom (1990), *Governing the Commons* (Cambridge).

5. Howard Rheingold (2002), *Smart Mobs: The Next Social Revolution *(Basic Books).

6. Clay Shirky (2009), *Here Comes Everybody* (Penguin Books).

### GOV 385L • Time-Series Analysis

######
39105 •
Spring 2013

Meets
MW 1230pm-200pm BAT 1.104

show description
**Prerequisites**

Statistical Analysis in Political Science II or its equivalent

** **

**Course Description**

This course is designed to examine the formal and statistical structure of techniques useful for analyzing dynamic processes. Subtopics include difference equations; stationary ARMA processes; persistent and/or nonstationary processes including integrated, fractionally integrated, and near-integrated processes; the estimation and forecasting of time series single equation regression; cointegration and error correction; Granger causality and vector autoregression; time-varying parameter regression, and time-series cross-section models.

**Grading Policy**

- Homework Assignments (20%)
- Project/Paper Proposal (20%)
- Final Project/Paper (60%)

**Required Texts**:

- Walter Enders. 2009.
*Applied Econometric Time Series*, 3e. Wiley. - Patrick T. Brandt and John T. Williams. 2007.
*Multiple Time Series*. Sage. - A packet of journal articles and book chapters.

**Recommended Texts**

- C. Chatfield. 1996.
*The Analysis of Time Series: An Introduction*, 5e. Chapman and Hall. - Samuel Goldberg. 2010.
*Introduction to Difference Equations: With Illustrative Examples from Economics, Psychology, and Sociology*. Dover. - John M. Gottman. 1981.
*Time-Series Analysis: A Comprehensive Introduction for Social Scientists*. Cambridge - Damodar N. Gujarati. 2003.
*Basic Econometrics*, 4e. McGraw-Hill & Irwin. - G. S. Maddala and In-Moo Kim. 1998. Unit Roots, Cointegration, and Structural Change. Cambridge.
- Richard McCleary and Richard A. Hay, Jr. 1980.
*Applied Time Series Analysis for the Social Sciences*. Sage. - Robert S. Pindyck and Daniel L. Rubinfeld. 1997.
*Econometric Models and Economic Forecasts*, 4e. McGraw-Hill.

### GOV 350K • Statistical Anly In Polit Sci

######
38705 •
Fall 2012

Meets
MW 300pm-430pm BUR 208

show description
**Course Description**

**Grading Policy**

Homework Assignments (6-7 sets): 30%

In-Class Midterm Exam: 30%

In-Class Final Exam: 30%

Instructor Discretion (Attendance, Participation, etc.): 10%

**Required Texts**

*Introductory Statistics*, 5th Ed. Wiley. (Or 4th Ed., *Introductory Statistics for Buisness and Economics*, 1990, which is the same as the 5th Ed.)

**Optional Texts**

* S. B. Green and N. J. Salkind, 2011. *Using SPSS for Windows and Macintosh: Analyzing and Understanding Data*, 6th Ed. Prentice Hall.

### GOV 385L • Advanced Statistical Analysis

######
38925 •
Fall 2012

Meets
TTH 1230pm-200pm MEZ 2.120

show description
**Prerequisites**

Statistical Analysis in Political Science II or its equivalent.

**Course Description**

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, and other models depending on your interests. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MATHEMATICA for mathematical analysis.

**Grading Policy**

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By the end of October, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

**Required Texts**

* S. R. Eliason. 1993. *Maximum Likelihood Estimation: Logic and Practice.* Sage.

* G. King.1998. *Political Methodology: The Likelihood Theory of Statistical Inference*.

Michigan.

* T. F. Liao. 1994. *Interpreting Probability Models*. Sage.

* A packet of journal articles and book chapters.

**Strongly Recommended Texts**

* W. H. Greene. 2012. *Econometric Analysis*. 7th ed. Pearson & Prentice Hall.

* J. S. Long and J. Freese. 2006. *Regression Models for Categorical Dependent*

*Variables Using Stata*. 2nd ed. Stata Press.

### GOV 355M • Human Behav As Rational Actn

######
38710 •
Spring 2012

Meets
MWF 100pm-200pm PAR 201

show description
**Course Description**

**Course Requirements**

Upper-division standing required. 6 semester hours of lower-division coursework in government.

**Grading Policy**

1. First Paper (6-8 pages): 25% 2. Second Paper (7-9 pages): 25%3. Third Paper (8-10 pages): 30% 4. Presentation: 10%5. Attendance: 10%

**Texts**

1. Thomas C. Schelling (1978), Micromotives and Macrobehavior (Norton).

2. Robert Axelrod (1984), The Evolution of Cooperation (Basic Books).

3. Dennis Chong (1991), Collective Action and the Civil Rights Movement (Chicago).

4. Elinor Ostrom (1990), Governing the Commons (Cambridge).

5. Howard Rheingold (2002), Smart Mobs: The Next Social Revolution (Basic Books)

### GOV 380R • Math Methods For Pol Analysis

######
38895 •
Spring 2012

Meets
MW 1100am-1230pm BAT 1.104

show description

**Course Description**

This course introduces the mathematical concepts and methods essential for multivariate statistical analysis and formal political theory. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, constrained optimization, and difference and differential equations. Applications in multivariate statistical analysis include multiple regression, principal component analysis, factor analysis, etc., and their estimation in matrix form. Applications in formal political theory include equilibrium analysis, dynamic analysis, and spatial analysis.

**Course Requirements**

None

**Grading Policy**

1. Homework Assignments: 40%

2. Final Project: 60%

**Texts**

1. Alpha C. Chiang and Kevin Wainwright. 2004. *Fundamental Methods of Mathematical Economics*, 4th ed. McGraw-Hill/Irwin.

2. J. Douglas Carroll and Paul E. Green. 1997. *Mathematical Tools for Applied Multivariate Analysis.* Revised ed. Academic Press.

3. (Optional) Jeff Gill. 2006. *Essential Mathematics for Political and Social Research*. Cambridge.

4. (Optional) John Fox. 2009. *A Mathematical Primer for Social Statistics.* Sage.

### GOV 350K • Statistical Anly In Polit Sci

######
38725 •
Fall 2011

Meets
MW 330pm-500pm BUR 208

show description
Course Description

Grading Policy

Homework Assignments (6-7 sets): 30% In-Class Midterm Exam: 30% In-Class Final Exam: 30%Instructor Discretion (Attendance, Participation, etc.): 10%

Required Texts

* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)

Optional

* S. B. Green and N. J. Salkind, 2011. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 6th Ed. Prentice Hall.

### GOV 385L • Advanced Statistical Analysis

######
38935 •
Fall 2011

Meets
TTH 1100am-1230pm BAT 1.104

show description
Course Description

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, models for time-series cross-section data, and models for hierarchical data. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MAPLE or MATHEMATICA for symbolic algebra.

Course Requirements

Statistical Analysis in Political Science II or its equivalent

Grading Policy

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By Week 8, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

Required Texts:

* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference. Michigan.* T. F. Liao. 1994. Interpreting Probability Models. Sage.* A packet of journal articles and book chapters.

Strongly Recommended:

* W. H. Greene. 2012. Econometric Analysis. 7th ed. Pearson & Prentice Hall.* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent Variables Using Stata. 2nd ed. Stata Press.

### GOV 350K • Statistical Anly In Polit Sci

######
38920 •
Spring 2011

Meets
MW 330pm-500pm PAR 201

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This course introduces basic concepts and methods of statistics. Unlike the typical elementary statisticalcourses you may have taken, the emphasis here will be on applications in political science. The objective ofthis course is to help students acquire the literacy for understanding political science literatures based on thescientific approach, as well as to prepare interested students for more advanced methods courses.Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution,point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation,and simple regression. Computing will be an integral part of this course. You will use SPSS to analyze datafrom Gallup Survey, General Social Survey, and/or National Election Study in homework assignments. Inparticular, you will be asked to replicate results reported in journal articles and book chapters. You are alsoencouraged to develop and work out your own research problems.

### GOV 355M • Human Behav As Rational Actn

######
38935 •
Spring 2011

Meets
MWF 100pm-200pm PAR 201

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The term “rational action” as used in the economic approach is generally equated with maximizing behavior. Individual human agents are assumed to have consistent and stable preferences over alternatives each of which is assigned some “utility.” Maximization entails choosing the course of action that yields the highest expected utility. One is rational to the extent one uses the best means to achieve one’s goals.In this course we will learn a variety of social and political models based on such a notion of individual rationality and to investigate the collective consequences that can be logically inferred from its assumptions. In particular, we will find through the “Prisoner’s Dilemma,” the “Tragedy of the Commons,” and the “Free-Rider Problem” a contrast between rational man and irrational society. Self-serving behavior of individuals does not usually lead to collectively satisfactory results.So this course is about the stories of the Prisoners, the Herdsmen, and the Free-Riders. As a matter of fact, we will show that the Dilemma, the Tragedy, and the Problem share essentially the same mathematical structure, and hence they are essentially the same story - a story about human destiny. We will also introduce the various approaches that have been proposed for the escape from such a destiny.Course RequirementsUpper-division standing required.6 semester hours of lower-division coursework in government.

### GOV 385L • Advanced Statistical Analysis

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38810 •
Fall 2010

Meets
TTH 1100am-1230pm MEZ 2.120

show description
Course Description

In this course we will study some advanced statistical analyses, including models with categorical or limited dependent variable, event count models, event history models, models for time-series cross-section data, and models for hierarchical data. Most of these models rely on the maximum likelihood method of estimation, and hence we will first discuss probability distributions and statistical estimation theory, with an emphasis on the MLE. We will use STATA for statistical analysis and MAPLE for symbolic algebra.

Course Requirements

Statistical Analysis in Political Science II or its equivalent

Grading Policy

You are required to write a research paper based on a statistical procedure introduced in this class. The topic of the paper is your own choice, but you should discuss your ideas with the instructor early in the semester to obtain his approval. Depending on substantive merits, topics based “simplistic” methods may not be acceptable. By Week 8, you should turn in a paper proposal (5-10 pages) laying out your theoretical arguments, describing your data, and presenting your research design. You should work closely with the instructor in developing ideas, formulating models, acquiring data, and carrying out the analyses. Your grade will be based on the end result as well as your interaction with the instructor while working on this paper. There will be homework assignments and/or exams as the instructor deems necessary.

Required Texts:

* S. R. Eliason. 1993. Maximum Likelihood Estimation: Logic and Practice. Sage.

* G. King.1998. Political Methodology: The Likelihood Theory of Statistical Inference.

Michigan.

* T. F. Liao. 1994. Interpreting Probability Models. Sage.

* A packet of journal articles and book chapters.

Strongly Recommended:

* J. M. Box-Steffensmeier and B. S. Jones. 2004. Event History Analysis. Cambridge.

* W. H. Greene. 2008. Econometric Analysis. 6th ed. Pearson & Prentice Hall.

* J. S. Long and J. Freese. 2006. Regression Models for Categorical Dependent

Variables Using Stata. 2nd ed. Stata Press.

### GOV 391J • Statistical Anly In Pol Sci I

######
38870 •
Fall 2010

Meets
TTH 200pm-330pm BUR 124

show description
Course Description

This course introduces basic concepts and methods of statistics. Unlike the typical elementary statistical courses you may have taken, the emphasis here will be on applications in political science. The objective of this course is to help students acquire the literacy for understanding political science literatures based on the scientific approach, as well as to prepare interested students for more advanced methods courses.

Topics include descriptive statistics, probability and probability distributions, sampling, sampling distribution, point estimation, confidence intervals, hypothesis testing, analysis of variance, contingency tables, correlation, and simple regression. Computing will be an integral part of this course. You will use SPSS to analyze data from Gallup Survey, General Social Survey, and National Election Study in homework assignments. In particular, you will be asked to replicate results reported in journal articles and book chapters. You are also encouraged to develop and work out your own research problems.

Course Requirements

Grading Policy

Homework Assignments (5-7 sets): 30%

In-Class Midterm Exam: 30%

In-Class Final Exam: 30%

Instructor Discretion (Attendance, Participation, etc.): 10%

Required Texts

* T. H. Wonnacott and R. J. Wannacott. 1990. Introductory Statistics, 5th Ed. Wiley. (Or 4th Ed., Introductory Statistics for Buisness and Economics, 1990, which is the same as the 5th Ed.)

Optional

* S. B. Green and N. J. Salkind, 2008. Using SPSS for Windows and Macintosh: Analyzing and Understanding Data, 5th Ed. Prentice Hall.