## Courses

#### GOV 350K • Stat Anly In Poli Sci-Wb

###### 38610 • Spring 2021

Meets TTH 2:00PM-3:30PM

Internet; Synchronous

QR

Elementary statistical techniques and their applications to problems in political science.

#### GOV 350K • Stat Anly In Poli Sci-Wb

###### 38615 • Spring 2021

Meets TTH 5:00PM-6:30PM

Internet; Synchronous

QR

Elementary statistical techniques and their applications to problems in political science.

#### GOV 355J • Human Behav Rational Action-Wb

###### 38645 • Spring 2021

Meets MW 4:00PM-5:30PM

Internet; Synchronous

QRWr

An economic approach in studying rational action.

#### GOV 355J • Human Behav Rational Action-Wb

###### 37474 • Fall 2020

Meets TTH 12:30PM-2:00PM

Internet; Synchronous

QRWr

An economic approach in studying rational action.

#### GOV 385L • Advncd Statistical Analysis-Wb

###### 37705 • Fall 2020

Meets TTH 5:00PM-6:30PM

Internet; Synchronous

#### GOV 385L • Panel/Multilevel Data Anly-Wb

###### 37720 • Fall 2020

Meets MW 4:00PM-5:30PM

Internet; Synchronous

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

###### 37985 • Spring 2020

Meets TTH 2:00PM-3:30PM PAR 1

QR

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 or R 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.

#### GOV 355J • Human Behav Rational Action

###### 38015 • Spring 2020

Meets MWF 2:00PM-3:00PM MEZ 1.120

QRWr

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.

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

###### 38205 • Spring 2020

Meets TTH 5:00PM-6:30PM MEZ 1.118

(also listed as SDS 381)

This course introduces the mathematical concepts and methods essential for multivariate statistics and data science techniques. Mathematical topics include reviews of basic calculus and linear algebra, eigenvalues and eigenvectors, quadratic forms, vector and matrix differentiation, unconstrained optimization, and constrained optimization. Applications in statistics and data science include matrix representation of multiple regression, OLS and MLE in matrix form, factor analysis, principal component analysis (PCA), singular value decomposition (SVD), etc.

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

###### 37550 • Fall 2019

Meets MWF 1:00PM-2:00PM PHR 2.114

QR

**Semester Fall 201****9**

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

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

MWF 1:00-2:00pm PHR 2.114 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 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*__,__ 7^{th} Ed. Prentice Hall.

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

###### 37555 • Fall 2019

Meets TTH 2:00PM-3:30PM PHR 2.116

QR

**Semester Fall 201****9**

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

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

TTH 2:00-3:30pm PHR 2.116 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 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*__,__ 7^{th} Ed. Prentice Hall.

#### GOV 385L • Advanced Statistical Analysis

###### 37825 • Fall 2019

Meets TW 5:00PM-6:30PM MEZ 1.120

(also listed as SDS 385)

**Semester Fall 201****9**

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

**SDS 385.14 – Title** Maximum Likelihood Estimation

Substantial Writing Component: NO

**Unique Days Time Bldg/Room Instructor**

TW 5:00-6:30p MEZ 1.120 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 and/or R 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*. 3^{nd} 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.

* A packet of journal articles and book chapters.

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

###### 38280 • Spring 2019

Meets TTH 2:00PM-3:30PM MEZ 1.216

QRWr

Please check back for updates.

#### GOV 385L • Panel/Multilevel Data Anly

###### 38515 • Spring 2019

Meets TTH 5:00PM-6:30PM MEZ 1.210

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

###### 38490 • Fall 2018

Meets TTH 2:00PM-3:30PM PHR 2.114

QR

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

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

38490 TTH 2:00-3:30pm PHR 2.114 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*__,__ 7^{th} Ed. Prentice Hall.

#### GOV 385L • Advanced Statistical Analysis

###### 38740 • Fall 2018

Meets TTH 5:00PM-6:30PM MEZ 1.210

(also listed as SDS 385)

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

**SDS 385.14 – Title** Maximum Likelihood Estimation

Substantial Writing Component: NO

**Unique Days Time Bldg/Room Instructor**

38740 TTH 5:00-6:30p MEZ 1.210 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 and/or R 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*. 3^{nd} 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.

* A packet of journal articles and book chapters.

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

###### 38275 • Spring 2018

Meets TTH 2:00PM-3:30PM GDC 2.210

QRWr

**GOV 355M **: Human Behavior as Rational Action

Writing Flag & Quantitative Reasoning Flag

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).

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

###### 38464 • Spring 2018

Meets TTH 5:00PM-6:30PM MEZ 1.208

(also listed as SDS 381)

**GOV 380R**: Mathematical Methods for Political Analysis

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 and spatial analysis.

**Course Requirements**

Statistical Analysis in Political Science I&II (or, equivalently, Basic Statistics & Regression)

**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.

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

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

###### 38715 • Fall 2017

Meets TTH 2:00PM-3:30PM BUR 220

QR

**Semester Fall 201****7**

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

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

38715 TTH 2:00-3:30pm BUR 220 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*__,__ 7^{th} Ed. Prentice Hall.

#### GOV 385L • Advanced Statistical Analysis

###### 38925 • Fall 2017

Meets MW 5:00PM-6:30PM MEZ 1.210

(also listed as SDS 385)

**Semester Fall 201****7**

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

**SDS 385.14 – Title** Maximum Likelihood Estimation

Substantial Writing Component: NO

**Unique Days Time Bldg/Room Instructor**

38925/57080 MW 5:00-6:30p BAT 1.104 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*. 3^{nd} 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.

* A packet of journal articles and book chapters.

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

###### 38685 • Spring 2017

Meets TTH 11:00AM-12:30PM SZB 286

QRWr

**Semester Spring 2017**

**GOV 355M – Title**: Human Behavior as Rational Action

Writing Flag & Quantitative Reasoning Flag

** **

**Unique Days Time Bldg/Room Instructor**

38685 TTH 11:00-12:30pm BEN 1.126 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).

#### GOV 385L • Panel/Multilevel Data Anly

###### 38929 • Spring 2017

Meets T 3:30PM-6:30PM BAT 5.102

**The University of Texas at Austin**

** **

Government 385L

# Panel and Multilevel Data Analysis

Spring 2017

Tse-Min Lin and Christopher Wlezien

Tuesdays 3:30-6:30

tml@austin.utexas.edu and Wlezien@austin.utexas.edu

**Course Description**

The course provides a detailed introduction to pooled time series cross section (TSCS) data analysis and multilevel data analysis. To begin with, it focuses on the techniques for analysis of various TSCS data sets, from those where the number of time series observations exceeds the number of cross sectional units to those where the number of cross sectional units exceeds the number of time serial observations. The course then turns to multilevel (ML) data, in which analysis explicitly models the effects of units within which observations are contained. In both parts of the course, there will be an emphasis both on both the logic of analysis and estimation, the latter of which will involve use of Stata software.

**Course Format**

All students are required to do a research paper. This should contribute to political science knowledge, not (necessarily) TSCS or ML methodology per se. The paper needs to be in the form of a journal article and ready for submission. Since this is a methods course, you are encouraged to choose a topic that relates to another class or even a paper that that could use a more sophisticated re-analysis. As it will be prepared for journal submission, the paper should be written for a general audience and need not delve too deeply into methodological issues.

**Grades**

The main assignment for this class is the preparation of an original research paper, about which more detailed information will be provided in class.

Performance in the class likely will be assessed as follows:

25% General class performance

75% Research paper

- 5% Hypothesis
- 20% Proposal
- 50% Final Paper.

NOTE: Although we do not plan on having a final examination, because we think it distracts from the research paper, we reserve the right to add one if necessary—it depends entirely on student performance in class.

**Readings**

The course readings will include two books:

Hsiao, Cheng. 2014. *Analysis of Panel Data*, 3^{rd} Ed. Cambridge University Press.

D. A. Luke. 2004. *Multilevel Modeling*. Sage Publications.

Numerous articles and book chapters also will be required.

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

###### 38450 • Fall 2016

Meets MWF 2:00PM-3:00PM PHR 2.114

QR

**Semester Fall 201****6**

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

Quantitative Reasoning Flag

**Unique Days Time Bldg/Room Instructor**

38450 MWF 2:00-3:00pm PHR 2.114 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

###### 38680 • Fall 2016

Meets MW 5:00PM-6:30PM BAT 1.104

(also listed as SDS 385)

**Semester Fall 201****6**

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

**SDS 385.14 – Title** Maximum Likelihood Estimation

Substantial Writing Component: NO

**Unique Days Time Bldg/Room Instructor**

38680/56970 MW 5:00-6:30p BAT 1.104 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.

* A packet of journal articles and book chapters.

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

###### 37940 • Spring 2016

Meets TTH 2:00PM-3:30PM CLA 1.102

QRWr

**Semester Spring 2016**

**GOV 355M – Title**: Human Behavior as Rational Action

Writing Flag & Quantitative Reasoning Flag

** **

**Unique Days Time Bldg/Room Instructor**

37940 TTH 2:00-3:30pm CLA 1.102 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).

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

###### 38110 • Spring 2016

Meets TTH 5:00PM-6:30PM BAT 1.104

(also listed as SDS 381)

**Semester**

**Spring 2016**

**GOV 380R – Title**: Mathematical Methods for Political Analysis

** **

**Unique Days Time Bldg/Room Instructor**

38110 TTH 5:00PM - 6:30 PM BAT 1.104 LIN

**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 and spatial analysis.

**Course Requirements**

Statistical Analysis in Political Science I&II (or, equivalently, Basic Statistics & Regression)

**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.

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

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

###### 37744 • Fall 2015

Meets TTH 2:00PM-3:30PM BUR 136

QR

**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 5:00PM-6:30PM MEZ 4.144

(also listed as SDS 385)

**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 11:00AM-12:30PM BUR 112

QR

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 3:30PM-5:00PM MEZ 1.216

QRWr

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 5:00PM-6:30PM MEZ 1.204

(also listed as SDS 385)

**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 3:30PM-6:30PM GAR 1.134

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 3:30PM-5:00PM MEZ 1.216

Wr
C2

**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 12:30PM-2:00PM BAT 1.104

**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 1:00PM-2:00PM BUR 208

**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 5:00PM-6:30PM MEZ 1.204

(also listed as SSC 385)

**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 2:00PM-3:30PM MEZ 1.216

Wr
C2

**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 12:30PM-2:00PM BAT 1.104

**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 3:00PM-4:30PM BUR 208

**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

###### 38925 • Fall 2012

Meets TTH 12:30PM-2:00PM MEZ 2.120

(also listed as SSC 385)

**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 1:00PM-2:00PM PAR 201

Wr
C2

**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.

**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 11:00AM-12:30PM BAT 1.104

(also listed as SSC 384)

**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 3:30PM-5:00PM BUR 208

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

* 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 11:00AM-12:30PM BAT 1.104

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 3:30PM-5:00PM PAR 201

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 1:00PM-2:00PM PAR 201

Wr
C2

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

###### 38810 • Fall 2010

Meets TTH 11:00AM-12:30PM MEZ 2.120

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 2:00PM-3:30PM BUR 124

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.

#### GOV 355M • Hum Behav As Rational Actn-W

###### 38845 • Spring 2010

Meets TTH 3:30PM-5:00PM GAR 3.116

C2

Please check back for updates.

#### GOV 385L • Advanced Statistical Analysis

###### 39390 • Fall 2009

Meets TTH 11:00AM-12:30PM MEZ 2.120

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

###### 38295 • Spring 2009

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

#### GOV 355M • Hum Behav As Rational Actn-W

###### 38310 • Spring 2009

Meets TTH 2:00PM-3:30PM GAR 3.116

C2

Please check back for updates.

#### GOV 385L • Advanced Statistical Analysis

###### 39670 • Fall 2008

Meets MW 11:00AM-12:30PM MEZ 2.120

#### GOV 355M • Hum Behav As Rational Actn-W

###### 39330 • Spring 2008

Meets TTH 3:30PM-5:00PM GAR 3.116

C2

Please check back for updates.

#### GOV 385L • Advanced Statistical Analysis

###### 40285 • Fall 2007

Meets T 11:00AM-12:30PM MEZ 2.120

#### GOV 355M • Hum Behav As Rational Actn-W

###### 38815 • Spring 2007

Meets TTH 2:00PM-3:30PM MEZ 1.120

C2

Please check back for updates.

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

###### 39745 • Fall 2006

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

#### GOV 385L • Advanced Statistical Analysis

###### 39969 • Fall 2006

Meets W 3:30PM-6:30PM MEZ 2.120

#### GOV 355M • Hum Behav As Rational Actn-W

###### 37810 • Spring 2006

Meets TTH 11:00AM-12:30PM BUR 220

C2

Please check back for updates.

#### GOV 391L • Statistical Anly In Pol Sci II

###### 38230 • Spring 2006

Meets TTH 2:00PM-3:30PM BUR 232

Statistical Analysis in Political Science II.

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

###### 37695 • Fall 2005

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

#### GOV 355M • Hum Behav As Rational Actn-W

###### 36355 • Spring 2005

Meets TTH 3:30PM-5:00PM BUR 212

C2

Please check back for updates.

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

###### 37345 • Fall 2004

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

#### GOV 385L • Time-Series Analysis

###### 35992 • Fall 2003

Meets TTH 3:30PM-5:00PM BUR 124

#### GOV 391L • Statistical Anly In Pol Sci II

###### 35075 • Spring 2003

Meets TTH 11:00AM-12:30PM ENS 145

Statistical Analysis in Political Science II.

#### GOV 391L • Statistical Anly In Pol Sci II

###### 35000 • Spring 2002

Meets TTH 11:00AM-12:30PM ENS 145

Statistical Analysis in Political Science II.

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

###### 35815 • Fall 2001

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

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

###### 35490 • Fall 2000

Meets TTH 11:00AM-12:30PM BUR 220

Elementary statistical techniques and their applications to problems in political science.

#### GOV 391L • Statistical Anly In Pol Sci II

###### 34715 • Spring 2000

Meets TTH 2:00PM-3:30PM UTC 1.136

Statistical Analysis in Political Science II.