College of LS&A

Spring/Summer 2002 Course Guide

Note: You must establish a session for the correct term (Spring, Summer, or Spring/Summer 2002) on wolverineaccess.umich.edu in order to use the link "Check Times, Location, and Availability". Once your session is established, the links will function.

Courses in Political Science

This page was created at 6:40 PM on Sun, Jun 30, 2002.


Summer Half-Term Courses


POLSCI 414. The Politics of Civil Liberties and Civil Rights.

Section 201.

Instructor(s): John Min Kang (johnkang@umich.edu)

Prerequisites: Two courses in political science. (3). May be repeated twice, for a total of six credits.

Credits: (3).

Course Homepage: No homepage submitted.

This course examines civil rights and civil liberties from the perspective of Supreme Court opinions in various areas. We'll read cases involving First Amendment issues (like religious expression and anti-government speech); Substantive Due Process issues (like abortion and euthanasia); Equal Protection issues (like gender and racial discrimination); and more. We'll also read some classic works on political philosophy to give us some idea of what these cases might mean in the larger universe of political life.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 419 / CAAS 418. Black Americans and the Political System.

Section 201.

Instructor(s): Ruth Nicole Brown (nikkib@umich.edu)

Prerequisites: Two courses in political science; AAS 201 recommended. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course will focus on the relationship between African Americans and the political system. We will explore issues of representation, participation, and activism in both a historical and contemporary context. There will be constant attention given to how different meanings of race, gender, class, and sexuality matter in the political experiences of African Americans.

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POLSCI 447 / RELIGION 447. Comparative Studies in Religion and Politics.

Section 201.

Instructor(s): Melynda J Price (melyndap@umich.edu)

Prerequisites: (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course takes a survey approach to understanding some of the major linkages between religion and religious action to politics. The course will sample readings from the US, Latin America, and the Middle East with a goal toward understanding some of the major trends in the increased role of religion throughout the world since the 1970's. There will be a large focus on the historical origins of fundamentalism and moving beyond media images to tie together the commonalities between "fundamenatalist" movements globally.

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POLSCI 451 / JUDAIC 451. The Politics and Culture of Modern East European Jewry.

Section 201.

Instructor(s):

Prerequisites: A course in East European and/or Jewish history, and Comparative Politics is recommended. (3).

Credits: (3).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

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POLSCI 591. Advanced Internship in Political Science.

Section 201.

Instructor(s):

Prerequisites: Two courses in political science at the 400-level or above and concentration in political science; or graduate standing. Permission of supervising instructor and review by the Department's internship advisor. (2-6). No more than four credits of internship may be included as part of a concentration plan in political science. (EXPERIENTIAL). All internship courses may be elected for a maximum total of eight credits.

Credits: (2-6).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

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POLSCI 592. Advanced Internship in Political Science.

Section 201 CLASS TO TAKE PLACE IN WASHINGTON. D.C. DATES TO BE ANNOUNCED. (3 CREDITs.)

Instructor(s): Charlene Allen (chjallen@umich.edu)

Prerequisites: Two courses in political science at the 400-level or above and concentration in political science; or graduate standing. Permission of supervising instructor and review by the Department's internship advisor. (2-6). No more than four credits of internship may be included as part of a concentration plan in political science. (EXPERIENTIAL). All internship courses may be elected for a maximum total of eight credits.

Credits: (2-6).

Course Homepage: No homepage submitted.

This course is a seminar designed to take advantage of your work experiences in Washington. Therefore, your primary assignment will be to produce a research paper on a subject related to your internship work.

Because this course is a small seminar, it depends heavily on the participation and contributions of class members. Thus, attendance and active participation are required. The readings for the course will be related to American government, with a focus on policy making, Congress, the Bureaucracy, etc.

As in previous summer meetings of this course, we will meet once a week for several hours, Tuesday 6-9pm. We will have several guest speakers in addition to our own discussions and in-class activities. We meet for 8 weeks starting the first week of June through the fourth week of July (week of June 2 thru week of July 21).

In order to get permission to register, send me an email telling me about your internship plans and what prior coursework you have taken that makes you a good candidate for this course. Also, a limited number of scholarships are available for the course.

Charlene Allen chjallen@umich.edu

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POLSCI 594. Introduction to Statistics and Data Analysis I.

Section 211.

Instructor(s): Pedro Sanchez

Prerequisites: College algebra. ICPSR Summer Program. (2).

Credits: (2 in the half-term).

Course Homepage: No homepage submitted.

The only prerequisite for this course is skill in basic algebra. Participants who have weak mathematical backgrounds are advised to enroll in Mathematics for Social Scientists I simultaneously with this course. The instructional format for this four-week course is lecture combined with daily analyses performed by the participants, some using hand-held calculators and some using statistical software on a computer. Topics include: data acquisition, classification, and summarization; basic probability; random variables and their distributions; and confidence intervals and tests of hypotheses for means, variances, and proportions from one or two populations. The course will be taught at the level of the first 13 chapters of Applied Statistics by Neter, Wasserman, and Whitmore. Participants should bring calculators with additive memory and a square root function.

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POLSCI 595. Introduction to Statistics and Data Analysis II.

Section 222.

Instructor(s): Merle Barbara Feldbaum

Prerequisites: Pol. Sci. 594. ICPSR Summer Program. (2).

Credits: (2 in the half-term).

Course Homepage: No homepage submitted.

This course is a continuation of Introduction to Statistics and Data Analysis I, and that course or its equivalent is a prerequisite. Course content will include the study of regression, chi square, and analysis of variance. Other topics will be discussed as time permits. Each concept will be illustrated by numerous substantive examples drawn from social research. The course will be taught at the level of Neter et al., Applied Statistics.

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POLSCI 596. Introduction to Regression Analysis.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 6/24-7/19.

Instructor(s): Saundra Schneider

Prerequisites: Introductory statistics. ICPSR Summer Program. (3).

Credits: (3 in the half-term).

Course Homepage: No homepage submitted.

Students entering this workshop should have had at least one semester of basic introductory statistics. The workshop will provide an introduction to bivariate and multivariate regression models. Topics will include the development of the regression model, analysis of variance, parameter estimation, hypothesis testing, applications, and interpretation. The level of the course will be approximately that of Lewis-Beck's Applied Regression.

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POLSCI 692. Directed Reading.

Instructor(s):

Prerequisites: Graduate standing and permission of instructor required. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

A direct reading on a topic of the student's choice.

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POLSCI 695. Regression Analysis.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETs 6/24-7/19.

Instructor(s): Timothy McDaniel

Prerequisites: Introductory statistics and a background in elementary mathematics sufficient for the study of matrix algebra, and Pol. Sci. 599. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

The prerequisites for the workshop are an introductory course in applied statistics at the level of Neter et al., Applied Statistics, and a background in elementary mathematics sufficient for the study of matrix algebra. The content of this course will include the nature of a linear model, least squares and maximum likelihood estimation, analysis of residuals, the general linear model, violation of assumptions (multicollinearity, heteroskedasticity, autocorrelation, measurement error, specification error), models with dummy variables, analysis of variance, and analysis of covariance. These concepts will be motivated by and illustrated with numerous substantive examples. Although knowledge of matrix arithmetic is not a prerequisite for this course, some concepts in matrix algebra will be introduced as appropriate. Wonnacott and Wonnacott's Econometrics, Neter and Wasserman's Applied Linear Statistical Models, and Weisberg's Applied Regression Analysis are three of a large number of texts that could be used for this course.

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POLSCI 695. Regression Analysis.

Section 212.

Instructor(s): Regina M Baker

Prerequisites: Introductory statistics and a background in elementary mathematics sufficient for the study of matrix algebra, and Pol. Sci. 599. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

The prerequisites for the workshop are an introductory course in applied statistics at the level of Neter et al., Applied Statistics, and a background in elementary mathematics sufficient for the study of matrix algebra. The content of this course will include the nature of a linear model, least squares and maximum likelihood estimation, analysis of residuals, the general linear model, violation of assumptions (multicollinearity, heteroskedasticity, autocorrelation, measurement error, specification error), models with dummy variables, analysis of variance, and analysis of covariance. These concepts will be motivated by and illustrated with numerous substantive examples. Although knowledge of matrix arithmetic is not a prerequisite for this course, some concepts in matrix algebra will be introduced as appropriate. Wonnacott and Wonnacott's Econometrics, Neter and Wasserman's Applied Linear Statistical Models, and Weisberg's Applied Regression Analysis are three of a large number of texts that could be used for this course.

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POLSCI 695. Regression Analysis.

Section 213.

Instructor(s): Robert W Andersen

Prerequisites: Introductory statistics and a background in elementary mathematics sufficient for the study of matrix algebra, and Pol. Sci. 599. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

The prerequisites for the workshop are an introductory course in applied statistics at the level of Neter et al., Applied Statistics, and a background in elementary mathematics sufficient for the study of matrix algebra. The content of this course will include the nature of a linear model, least squares and maximum likelihood estimation, analysis of residuals, the general linear model, violation of assumptions (multicollinearity, heteroskedasticity, autocorrelation, measurement error, specification error), models with dummy variables, analysis of variance, and analysis of covariance. These concepts will be motivated by and illustrated with numerous substantive examples. Although knowledge of matrix arithmetic is not a prerequisite for this course, some concepts in matrix algebra will be introduced as appropriate. Wonnacott and Wonnacott's Econometrics, Neter and Wasserman's Applied Linear Statistical Models, and Weisberg's Applied Regression Analysis are three of a large number of texts that could be used for this course.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 695. Regression Analysis.

Section 222.

Instructor(s): Brian Michael Pollins

Prerequisites: Introductory statistics and a background in elementary mathematics sufficient for the study of matrix algebra, and Pol. Sci. 599. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

The prerequisites for the workshop are an introductory course in applied statistics at the level of Neter et al., Applied Statistics, and a background in elementary mathematics sufficient for the study of matrix algebra. The content of this course will include the nature of a linear model, least squares and maximum likelihood estimation, analysis of residuals, the general linear model, violation of assumptions (multicollinearity, heteroskedasticity, autocorrelation, measurement error, specification error), models with dummy variables, analysis of variance, and analysis of covariance. These concepts will be motivated by and illustrated with numerous substantive examples. Although knowledge of matrix arithmetic is not a prerequisite for this course, some concepts in matrix algebra will be introduced as appropriate. Wonnacott and Wonnacott's Econometrics, Neter and Wasserman's Applied Linear Statistical Models, and Weisberg's Applied Regression Analysis are three of a large number of texts that could be used for this course.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 811. Advanced Multivariate Statistical Methods.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 6/24 - 7/19

Instructor(s): Razia Azen

Prerequisites: Graduate standing. (3).

Credits: (3).

Course Homepage: No homepage submitted.

A very strong background in statistics at least at the level of the ICPSR courses Regression Analysis and Mathematics for Social Scientists II is necessary for this course. The purpose of this four-week workshop is to discuss linear models that are useful for analyzing multivariate data. After briefly reviewing univariate linear models, the course will cover multivariate hypothesis testing, principal components analysis, discriminant analysis, canonical correlation analysis, multivariate analysis of variance, and factor analysis. The level and breadth of coverage is roughly equivalent to that found in the multivariate texts Cooley and Lohnes, Multivariate Data Analysis; Tatzuoka, Multivariate Analysis; and Johnson and Wichern, Applied Multivariate Statistical Analysis.

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POLSCI 812. Scaling and Dimensional Analysis.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22 - 8/16.

Instructor(s): William Jacoby

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

Participants who elect this course should have had an introductory course in applied statistics at about the level of Neter et al., Applied Statistics, and they should have a mathematical competency consistent with the content of the ICPSR course Mathematics for Social Scientists II. This workshop will focus on analytic techniques designed to provide geometric representations of data. Topics to be covered include brief examinations of measurement theory, Likert scaling, magnitude scaling, more detailed investigations of the unfolding model, factor analysis, and several varieties of multidimensional scaling. If time permits, several additional techniques will be covered, including cluster analysis and optimal scaling procedures. No single text satisfactorily covers all of these topics; instead, the class will rely on Davison's Multidimensional Scaling, articles from professional journals, and several of the Sage University Papers on Quantitative Applications in the Social Sciences (e.g., McIver and Carmine's Unidimensional Scaling, and Kim and Mueller's two volumes on factor analysis).

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POLSCI 813. Structural Equation (Causal) Modeling.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s):

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 814. Time Series Analysis.

Section 221 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): John Williams

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

Both the ICPSR courses Regression Analysis and Mathematics for Social Scientists II are prerequisites for this course. This four-week workshop begins by focusing on the autoregressive and moving average components of time series, and then turns to estimation of univariate time series models using the Box-Jenkins approach. Intervention analysis and more general transfer function models build on this tradition, often referred to as the statistical analysis of time series. The course then focuses on the econometric (regression) analysis of time series, historically quite distinct from the statistical tradition. In recent years, regression analysis has borrowed much from the statistical tradition, and the connections between the two are important for understanding how social scientists should analyze time series data. Analysis of integrated time series, including unit root econometrics and error correction models, focuses on recent econometric advances in dealing with nonstationary data. Mill's Time Series Analysis for Economists, McCleary and Hay's Applied Time Series Analysis for Social Scientists, and Harvey's Econometric Analysis of Time Series include much of the material that will be covered in this course.

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POLSCI 815. Categorical Analysis.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): Simon Cheng

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

"Which candidate did you vote for?" "Which diagnosis is correct given the patient's symptoms?" "Will that offender avoid crime in the future?" Responses to questions of this kind are recorded in unordered categories whose statistical analysis is the topic of this workshop. When observations from individual cases are available, they may be treated within a regression framework in which coefficients for the explanatory variables are found under the assumptions of linear probability, linear discriminant, probit, logit, multinomial logit, or conditional logit models. When individual cases have been grouped into a contingency table, cell proportions rather than individual responses constitute the dependent variable, and linear probability, log-linear, or logistic models may be employed. The statistical justification of models for both situations will be presented, and their application to survey data will be illustrated in class and through computer exercises. Participants should enter this workshop with an active working knowledge of the topics covered in Regression Analysis and Mathematics for Social Scientists II. Readings will be drawn from texts such as Agresti's Categorical Data Analysis and Long's Regression Models for Categorical and Limited Dependent Variables.

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POLSCI 816. (LISREL) Models: General Structural Equations.

Section 221 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): Douglas Edward Baer

Prerequisites: Multivariate statistics/Pol. Sci. 787. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

Individuals who enroll in this workshop should have taken the ICPSR courses Regression Analysis, Simultaneous Equation Models, Scaling and Dimensional Analysis, and Mathematics for Social Scientists II, or their equivalents. This course provides an introduction to estimation techniques for structural equation models that contain latent or unmeasured variables. These models, commonly referred to as "LISREL" models (named for the computer program most widely used to estimate them), are more general than the usual econometric/regression models. They allow for measurement error in the observed variables as well as multiple indicators for the latent variables. The "LISREL" models' relationships with measurement theory are discussed. Topics treated include path analysis, confirmatory factor analysis, and consequences of measurement error. Much of the content of the course is covered in Bollen's Structural Equations with Latent Variables.

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POLSCI 817. Advanced Analysis of Variance.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): Michael L Berbaum

Prerequisites: Aan introduction to analysis of variance and linear regression models/Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 818. Mathematical Models: Game Theory.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 6/24-7/19.

Instructor(s): Mark Fey

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course introduces individuals to one of the most important areas of decision theory, interactive choices between actors. The fundamental concepts linked with the criteria of individual rationality will be thoroughly explained and integrated into a broad overview of the theory of games. Individual topics will include discussions of both continuous and matrix games. Topics particularly relevant to matrix games will include two-person, n-person, and zero and non-zero sum, as well as cooperative and non-cooperative games. Applications to a variety of substantive fields will be discussed. The prerequisite for the workshop is an introductory course in applied statistics at the level of Neter et al., Applied Statistics.

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POLSCI 819. Mathematical Models: Rational Choice in a Social Context.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): James D Johnson

Prerequisites: An understanding of game theory modeling and a course in applied statistics, Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

"Rational choice theory" actually consists of a set of theories, usually but not always mathematical, that investigate the ways that actions taken by rational individual decision-makers can interact in often surprising ways to generate stable aggregate outcomes. This workshop is an introduction to rational choice theories and their uses in social science. It focuses on the logic of rational choice analysis in both explanatory and, to a lesser extent, normative contexts. The aims of the workshop are to impart the basic techniques of rational choice modeling and to explore the intuitive and theoretical issues that motivate and limit any use of those techniques. The workshop especially is concerned with matters of interpretation and empirical testing, and with the problem of determining just what any particular class of rational choice theories tells us about the social and political world and how it purports to do so. Topics include models of voting, bargaining, collective action, social norms, institutions, and even culture. Readings are drawn from economics, political science, sociology, and anthropology. Class format throughout combines lecture and discussion, but the balance shifts from the former to the latter as the session progresses. Although the workshop does not presuppose familiarity with either game theory or the mathematics needed to solve game-theoretic problems, some prior knowledge of those topics will be an advantage. Students interested in this workshop are strongly advised to take a game theory course prior to enrolling.

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POLSCI 820. Maximum Likelihood Estimation for Generalized Linear Models.

Section 211 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 6/24-7/19.

Instructor(s): Charles Franklin

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course introduces and develops a number of new and very useful statistical models that move beyond standard linear regression. Among the topics covered are logit and probit models for both binary and ordinal dependent variables, event count models, models for heteroskedastic regressions, and more. Maximum likelihood unifies these models by providing a single, coherent approach to estimation and a way of thinking about how data are generated. The background needed for the course is multiple regression in matrix form. Attendance at the Mathematics for Social Scientists II lectures should prove useful.

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POLSCI 822. Dynamic/Longitudinal Analysis.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETs 6/24 - 7/19.

Instructor(s):

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (2).

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 822. Dynamic/Longitudinal Analysis.

Section 231 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETs 6/24 - 7/19.

Instructor(s): Michael L Berbaum

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (2).

Credits: (2).

Course Homepage: No homepage submitted.

Longitudinal analysis is the study of short series of observations obtained from many respondents over time and is also referred to as panel analysis (of a cross-section of time series), or repeated measures, or growth curve analysis (polynomials in time), or multilevel analysis (where one level is a sequence of observations from respondent). Longitudinal analysis is used for panel surveys, experiments, and quasi-experiments in health and biomedicine, education and psychology, and the evaluation of prevention and treatment programs. This course treats the statistical basis and practical application of linear models for longitudinal normal data and generalized linear models for longitudinal binary, count, and ordinal data. The approach involves inclusion of random effects in linear models to reflect within-person cross-time correlation. Techniques for irregularly observed (unequally spaced) data will be covered. Other ICPSR courses focus on time series and structural equations approaches, including latent growth curve models, which are only briefly discussed in this course. The technical level will be at Track II, with interludes at Track III (matrix algebra, probability distributions). Examples and exercises will use both standard and special-purpose software. Participants should have a good understanding of linear regression or analysis of variance.

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POLSCI 822. Dynamic/Longitudinal Analysis.

Section 241 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETs 6/24 - 7/19.

Instructor(s):

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (2).

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 824. Non-Linear Systems II.

Section 202 Complex Systems Models in the Social Sciences. ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): Kenneth W Kollman (kkollman@umich.edu), Scott Page, Rick Riolo

Prerequisites: Regression analysis/Pol. Sci. 699. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

The nonlinear dynamics exhibited by complex systems often pose difficult problems for modelers of those systems, especially when the complex systems are adaptive. The growing availability of computers has led to a recent proliferation of "bottom-up, agent-based" models of complex adaptive systems. These models consist of a number of interacting agents, and each agent's behavior is governed by a small set of simple rules. However, the interaction of the agents can produce complex "emergent" structures and dynamic behaviors of individuals and groups. These lectures will give an introduction to bottom-up approaches to computer modeling and compare them to more traditional mathematical (analytical) approaches and to top-down computer models (e.g., typical macro-economic models). The lectures will also offer a survey of the field of Evolutionary Computation (EC), including a discussion of the role of EC in agent-based models. A number of social science applications will also be reviewed and analyzed.

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POLSCI 826. Computing for Social Science.

Section 201 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETS 6/24-7/19.

Instructor(s): Hawthorne Michael Robert

Prerequisites: ICPSR Summer Program. (2).

Credits: (2).

Course Homepage: No homepage submitted.

This series of integrated lectures covering various aspects of computer usage in the social sciences is designed so that a participant can attend a module in one topic without prior attendance at other lectures. However, students can obtain a broad overview of computer issues by attending the complete series. Initial lectures will introduce techniques of computing at ICPSR. In later lectures, three major statistical packages, SAS, SPSS, and Stata, will be discussed. Comparisons of the capabilities of these packages and other computing software will be developed. An abbreviated version of this course will also be offered during the second four-week session of the Program, when introductions to SPSS, SAS, and Stata will be repeated.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 826. Computing for Social Science.

Section 212.

Instructor(s): Phillip Ardoin

Prerequisites: ICPSR Summer Program. (2).

Credits: (2).

Course Homepage: No homepage submitted.

This series of integrated lectures covering various aspects of computer usage in the social sciences is designed so that a participant can attend a module in one topic without prior attendance at other lectures. However, students can obtain a broad overview of computer issues by attending the complete series. Initial lectures will introduce techniques of computing at ICPSR. In later lectures, three major statistical packages, SAS, SPSS, and Stata, will be discussed. Comparisons of the capabilities of these packages and other computing software will be developed. An abbreviated version of this course will also be offered during the second four-week session of the Program, when introductions to SPSS, SAS, and Stata will be repeated.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 827. Research Design for Social Science.

Section 201 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETs 6/24-7/19.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 827. Research Design for Social Science.

Section 211.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 827. Research Design for Social Science.

Section 213.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 827. Research Design for Social Science.

Section 214.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 827. Research Design for Social Science.

Section 222.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 827. Research Design for Social Science.

Section 223.

Instructor(s):

Prerequisites: ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 829. Mathematics for Social Science.

Section 201 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEET 6/24-7/19.

Instructor(s): Stephen G Bringardner

Prerequisites: Introductory statistics/Pol. Sci. 599. ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

This four-week series of lectures is designed to review those basic mathematical skills necessary for a meaningful understanding of elementary statistics, data analysis, and social methodology. Course content includes a discussion of mathematical notation, basic set theory, various number systems, the algebra of numbers, the notion of a function, several important classes of functions, and solutions to systems of linear equations. In addition, several approaches to the specification of probability will be examined, and some basic statistical concepts will be introduced. The general discourse will be at about the level of W.L. Bashaw's Mathematics for Statistics. This lecture series is most suitable as a review for those who have been exposed to this material previously, but it is also intended to serve as a brief and limited introduction.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 829. Mathematics for Social Science.

Section 202.

Instructor(s):

Prerequisites: Introductory statistics/Pol. Sci. 599. ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 829. Mathematics for Social Science.

Section 212 Review/Introductory Lectures on Matrix Algebra. ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEETS 7/22-8/16.

Instructor(s): Pedro Sanchez

Prerequisites: Introductory statistics/Pol. Sci. 599. ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

This lecture series is intended to provide a background in matrix algebra for participants in ICPSR workshops. Approximately nine one-hour lectures will be devoted to matrices and linear algebra. The lecture series is most suitable as a review for those who have been exposed to this material previously, but it is also intended to serve as a brief and limited introduction.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 829. Mathematics for Social Science.

Section 213.

Instructor(s):

Prerequisites: Introductory statistics/Pol. Sci. 599. ICPSR Summer Program. (2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 830. Advanced Topics in Social Research.

Section 201 ICPSRCOURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. MEET 6/24-7/19.

Instructor(s): Henry A Heitowit

Prerequisites: Permission of instructor. ICPSR Summer Program.(2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 830. Advanced Topics in Social Research.

Section 202.

Instructor(s): Henry A Heitowit

Prerequisites: Permission of instructor. ICPSR Summer Program.(2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 830. Advanced Topics in Social Research.

Section 211.

Instructor(s): Henry A Heitowit

Prerequisites: Permission of instructor. ICPSR Summer Program.(2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 830. Advanced Topics in Social Research.

Section 222.

Instructor(s): Henry A Heitowit

Prerequisites: Permission of instructor. ICPSR Summer Program.(2). May be repeated for credit.

Credits: (2).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 832. Mathematical Statistics for Social Science.

Section 222 Bayesian Methods for the Social and Behavioral Sciences. ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 6/24-7/19.

Instructor(s): Jefferson M Gill

Prerequisites: Regression Analysis/Pol. Sci. 699. ICPSR Summer Program.(3).

Credits: (3).

Course Homepage: No homepage submitted.

This course introduces the theoretical and applied foundations of Bayesian statistical analysis in a manner accessible to social and behavioral scientists. The Bayesian paradigm is ideally suited to the type of data analysis required of social scientists because it recognizes the mobility of population parameters, incorporates prior knowledge that researchers possess, and updates estimates as new data are observed. This course will introduce the basic principles of Bayesian statistics to students in the social and behavioral sciences without requiring an extensive background in mathematical statistics. Most of the examples will be drawn from sociology, political science, economics, marketing, psychology, public policy, and anthropology. The prerequisites for this course are a linear regression course and knowledge of matrix algebra. The emphasis will be on applying the principles to actual data-analytic problems of interest to participants rather than through textbook examples. The course will make extensive use of software that is in the public domain, yet is high in quality. The course includes basic topics such as setting up a probability model, conditioning on observed data, and the essential ideas behind likelihood inference and prediction. The fundamentals of Bayesian statistics are reviewed, including Bayes Law and prior and posterior distributions, as well as summarizing the model and checking sensitivity to the assumptions. Practical applications will be developed with a variety of parametric forms including so-called non-informative prior densities. All of the fundamental Bayesian simulation techniques will be reviewed including numerical integration, importance sampling, the EM algorithm, and the primary Markov Chain Monte Carlo algorithms: Gibbs sampling and Metropolis-Hastings. The text for the course will be Gill's Bayesian Methods for the Social and Behavioral Sciences.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 838. Mathematical Models: Advanced Game Theory.

Section 222 ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s):

Prerequisites: Regression Analysis/Pol. Sci. 699 and Game Theory/Pol. Sci. 818. ICPSR Summer Program.(3).

Credits: (3).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 841. Advanced Topics in Maximum Likelihood Estimation.

Section 222 Maximum Likelihood Estimation for Generalized Linear Models. ICPSR COURSE. FOR PERMISSION TO ENROLL CONTACT HENRY HEITOWIT, 998-9888. COURSE MEETS 7/22-8/16.

Instructor(s): Charles Franklin

Prerequisites: Poli. Sci. 821. ICPSR Summer Program. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course introduces and develops a number of new and very useful statistical models that move beyond standard linear regression. Among the topics covered are logit and probit models for both binary and ordinal dependent variables, event count models, models for heteroskedastic regressions, and more. Maximum likelihood unifies these models by providing a single, coherent approach to estimation and a way of thinking about how data are generated. The background needed for the course is multiple regression in matrix form. Attendance at the Mathematics for Social Scientists II lectures should prove useful.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 892. Directed Research.

Instructor(s):

Prerequisites: Graduate standing. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

Directed research on a topic of the student's choice.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 990. Dissertation/Precandidate.

Instructor(s):

Prerequisites: Election for dissertation work by doctoral student not yet admitted as a Candidate. Graduate standing. (1-4). (INDEPENDENT). May be repeated for credit.

Credits: (1-8; 1-4 in the half-term).

Course Homepage: No homepage submitted.

Election for dissertation work by doctoral student not yet admitted as a Candidate.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 995. Dissertation/Candidate.

Instructor(s):

Prerequisites: Graduate School authorization for admission as a doctoral Candidate. Graduate standing. (4). (INDEPENDENT). May be repeated for credit.

Credits: (8; 4 in the half-term).

Course Homepage: No homepage submitted.

Graduate School authorization for admission as a doctoral Candidate. N.B. The defense of the dissertation (the final oral examination) must be held under a full term Candidacy enrollment period.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor


Spring Half-Term Courses


POLSCI 401. Development of Political Thought: Modern and Recent.

Section 101.

Instructor(s): Eric S Kos (ekos@umich.edu)

Prerequisites: Junior standing or two courses in political science. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course will trace certain themes that help define the modern political perspective. In modern political thought, the self-regulating individual is the starting point for visualizing political order. Much of modern thought begins from the premise that individuals have rights antecedent to government; that no one is, either by nature or by divine appointment, in a position of political authority. Each of the writers explored in this course share the view that the purpose of politics is to secure freedom, but they differ sharply over what counts as genuine human freedom, both from each other and from more ancient political thinkers. With a close examination of these thinkers, and their understandings of freedom, equality, political obligation, the individual, and community, we shall be explore and make explicit our own political assumptions.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 413. American Constitutional Politics.

Section 101.

Instructor(s):

Prerequisites: Pol. Sci. 111, 410, or 411. (3).

Credits: (3).

Course Homepage: No homepage submitted.

No Description Provided. Contact the Department.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 423. Politics of the Metropolis.

Section 101.

Instructor(s): Laura E Evans (lauraee@umich.edu)

Prerequisites: Two courses in political science. (3).

Credits: (3).

Course Homepage: No homepage submitted.

This course explores the forces behind politics and policy in cities today. Course materials examine power structures within cities, external influences on urban affairs, and what urban government looks like as a result. In particular, this class addresses:

  1. who influences decision-making in cities,
  2. how federal policy affects cities,
  3. how suburbanization changed cities, and
  4. the ways race and poverty matter in urban affairs.

Political Science 423 should appeal to students interested in urban politics specifically, as well as to students interested in federalism, the role of institutions in American government, and the consequences of history for contemporary politics.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 448. Politics and Society in Latin America.

Section 101.

Instructor(s): Jose R Perales-Hernandez (jrph@umich.edu)

Prerequisites: Pol. Sci. 140 or 440; or a course on Latin America elected through another department. (3).

Credits: (3).

Course Homepage: No homepage submitted.

Analysis of social change and political conflict in contemporary Latin America. Topics considered include race, class, and stratification; the role of the military; religion and politics; and the nature and implications of economic dependence. From year to year, emphasis is given to different countries (i.e., Mexico, Venezuela, Cuba, Brazil, Argentina).

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

POLSCI 450. Political Change in the Developing World.

Section 101.

Instructor(s): Irfan Nooruddin (irfann@umich.edu)

Prerequisites: Any 100-level course in political science.

Credits:

Course Homepage: http://www.umich.edu/~irfann/teaching/450.htm

At the start of a new millennium, the world faces a profound moral dilemma. While citizens of the First World enjoy ever increasing incomes and comforts, the majority of the world's population suffer in abject poverty. Why are some nations rich while others remain mired in inescapable misery? In this course, we will examine theories of development with an eye to understanding the underlying causes of development and underdevelopment. The key thesis I will argue is that history and institutions matter, but we will examine alternative explanations too. Throughout, we will employ the theoretical lens of political economy to exploit the explanatory leverage generated at the intersections of politics and economics. (No background in economics is presumed). Finally, the purpose of the course is to engage in social science and not to serve as a forum for policy debate.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 591. Advanced Internship in Political Science.

Section 101 CLASS TO TAKE PLACE IN OTTAWA, CANADA - DATES TO BE ANNOUNCED. (3 CREDITs.)

Instructor(s):

Prerequisites: Two courses in political science at the 400-level or above and concentration in political science; or graduate standing. Permission of supervising instructor and review by the Department's internship advisor. (2-6). No more than four credits of internship may be included as part of a concentration plan in political science. (EXPERIENTIAL). All internship courses may be elected for a maximum total of eight credits.

Credits: (2-6).

Course Homepage: No homepage submitted.

Advanced Internship requires careful, individual planning between senior students in Political Science and individual faculty members who approve the internship and provide instruction. To register for the course, the student must complete the internship form and obtain an override to enter the course. The form is available at 611 Church Street, Suite 334.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 692. Directed Reading.

Instructor(s):

Prerequisites: Graduate standing and permission of instructor required. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

A direct reading on a topic of the student's choice.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 892. Directed Research.

Instructor(s):

Prerequisites: Graduate standing. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

Directed research on a topic of the student's choice.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 990. Dissertation/Precandidate.

Instructor(s):

Prerequisites: Election for dissertation work by doctoral student not yet admitted as a Candidate. Graduate standing. (1-4). (INDEPENDENT). May be repeated for credit.

Credits: (1-4).

Course Homepage: No homepage submitted.

Election for dissertation work by doctoral student not yet admitted as a Candidate.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 995. Dissertation/Candidate.

Instructor(s):

Prerequisites: Graduate School authorization for admission as a doctoral Candidate. Graduate standing. (4). (INDEPENDENT). May be repeated for credit.

Credits: (4).

Course Homepage: No homepage submitted.

Graduate School authorization for admission as a doctoral Candidate. N.B. The defense of the dissertation (the final oral examination) must be held under a full term Candidacy enrollment period.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor


Spring/Summer Term Courses


POLSCI 692. Directed Reading.

Instructor(s):

Prerequisites: Graduate standing and permission of instructor required. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

A direct reading on a topic of the student's choice.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 892. Directed Research.

Instructor(s):

Prerequisites: Graduate standing. (1-6). (INDEPENDENT).

Credits: (1-6).

Course Homepage: No homepage submitted.

Directed research on a topic of the student's choice.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 990. Dissertation/Precandidate.

Instructor(s):

Prerequisites: Election for dissertation work by doctoral student not yet admitted as a Candidate. Graduate standing. (1-8). (INDEPENDENT). May be repeated for credit.

Credits: (1-8; 1-4 in the half-term).

Course Homepage: No homepage submitted.

Election for dissertation work by doctoral student not yet admitted as a Candidate.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor

POLSCI 995. Dissertation/Candidate.

Instructor(s):

Prerequisites: Graduate School authorization for admission as a doctoral Candidate. Graduate standing. (8). (INDEPENDENT). May be repeated for credit.

Credits: (8; 4 in the half-term).

Course Homepage: No homepage submitted.

Graduate School authorization for admission as a doctoral Candidate. N.B. The defense of the dissertation (the final oral examination) must be held under a full term Candidacy enrollment period.

Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: 5, Permission of Instructor


Undergraduate Course Listings for POLSCI.


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