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The University of Texas at Dallas
Graduate Admissions

EPPS Course Descriptions

EPPS 6304 Advanced Analytic Techniques (3 semester hours) This course prepares students to use advanced methods in economic and policy analysis. Topics include matrices and matrix operations, input-output analysis, the Cobb-Douglas production function and linear programming. (3-0) R

EPPS 6310 Research Design I (3 semester hours) This course is the first in a two-course sequence devoted to the research enterprise and the study of data development strategies and techniques to facilitate effective statistical analysis. Topics generally covered include: (1) issues and techniques in social science research with emphasis on philosophy of science, theory testing, and hypothesis formulation; (2) measurement and data collection strategies, reliability and validity of measures and results, sampling, surveys; and (3) examination of qualitative versus quantitative research techniques, working with observational data, field research issues, and triangulation. (3-0) Y
EPPS 6313 Introduction to Quantitative Methods (3 semester hours) This introductory graduate-level statistics course is geared to the consumption of statistical methods commonly used in social science research. Topics include creating and interpreting graphical and tabular summaries of data, descriptive statistics, basic probability theory, sampling distributions, basic hypothesis testing (t-tests, chi-square tests, and analysis of variance), estimation of population parameters, confidence intervals and correlation. An introduction to regression analysis will also be provided. Topics are supported by computer-supported data analyses. (3 semester hours) (3-0) Y
EPPS 6316 Applied Regression (3 semester hours) This course provides a survey of the bivariate and multiple regression models estimated using Ordinary Least Squares (OLS), with an emphasis on using regression models to test social and economic hypotheses. This application-focused course presents examples drawn from economics, political science, public policy and sociology, introduces the basic concepts and interpretation of regression models, and basic methods of inference.  Topics are supported by computer-supported data analyses. Prerequisite: EPPS 6313. (3-0) Y
EPPS 6342 Research Design II (3 semester hours) This course is the second in a two-course sequence devoted to the study of data development strategies and techniques to facilitate effective statistical analysis. Topics generally covered include: the logic of causal inquiry and inference in the Economic, Political and Policy Sciences, the elaboration paradigm and model specification, anticipating and handling threats to internal validity, hierarchies of design structure (experimental, quasi-experimental and non-experimental): linking design structure to effect estimation strategies and analyzing design elements in published literature. Students will be required to select a research topic in consultation with the instructor and prepare a written comparative design analysis. EPPS 6310, EPPS 6316 or equivalents recommended.  (3-0) Y
EPPS 6346 Qualitative Research Methods (3 semester hours) this course provides an overview of qualitative research in the Economic, Political and Policy Sciences. Students will investigate the assumptions underlying qualitative research approaches and critically assess the strengths and weaknesses of such approaches. Possible topics may include participant observation, ethnographic interviewing, ethnomethodology, conversation analysis, case study, and the analysis of historical documents. (3-0) T
EPPS 6352 Evaluation Research Methods in the Economic, Political and Policy Sciences (3 semester hours) A review of research methods used in program evaluation, with an emphasis on public and non-profit social programs. Issues to be addressed include research design, appropriate performance standards, measurement and selection of individuals, sampling, data collectionand data analysis. (3-0) Y
EPPS 7304 Cost-Benefit Analysis (3 semester hours) Examines methods for measuring costs and benefits of public projects and policies, and the application of cost-benefit analysis to areas such as economic development, water resources, recreation, transportation, regulation, and the environment. (3-0) T
EPPS 7313 Descriptive and Inferential Statistics (3 semester hours) This course is designed to prepare students for the advanced quantitative methodology courses required of advanced degree students. The fundamentals of sampling design and measurement will be covered. Students will then develop an understanding of the principles by which a variety of statistical methodologies function, from simple, two-sample tests to more complex non-parametric and asymmetric methods. The course closes with an introduction to multiple regression. While the only pre-requisite is a sound foundation in algebra, some familiarity with the fundamentals of calculus and linear algebra will provide a stronger foundation for learning. Topics are supported by computer-supported data analyses using application-specific software. (3-0) Y
EPPS 7316 Regression and Multivariate Analysis (3 semester hours) This course provides a detailed examination of the multiple regression models estimated using Ordinary Least Squares (OLS), with an emphasis on using regression models to test social and economic hypotheses. Also covered are several special topics in regression analysis, including violations of OLS assumptions, the use of dummy variables, and fixed effects models. The course ends with an introduction to advanced topics in regression analysis, qualitative response models, and non-OLS approaches to estimation. Topics are supported by computer-supported data analyses using application-specific software. Prerequisite: EPPS 7313. (3-0) Y
EPPS 7318 Structural Equation and Multilevel (Hierarchical) Modeling (3 semester hours) An introduction to structural equation modeling (SEM) and multilevel modeling (MLM), sometimes called hierarchical linear or mixed modeling. SEM represents a general approach to the statistical examination of the fit of a theoretical model to empirical data. Topics include observed variable (path) analysis, latent variable models (e.g., confirmatory factor analysis), and latent variable SEM analyses. MLM represents a general approach to handling data that are nested within each other or have random components. Topics include dealing with two-level data that may be cross-sectional, such as students within classes, or longitudinal, such as repeated observations on individuals, firms or countries. EPPS 7316 or equivalent recommended. Prerequisite: ECON 6306 or ECON 6309 or EPPS 6316 or permission of instructor. (3-0) R
EPPS 7344 Categorical and Limited Dependent Variables (3 semester hours) This course examines several types of advanced regression models that are frequently used in policy analysis and social science research. The key similarity of these models is that they involve dependent variables that violate one or more of the assumptions of the Ordinary Least Squares (OLS) regression model. The main models examined in the course are binary logit and probit, multinomial logit, ordinal probit, tobit, and the family of Poisson regression models. All these models are estimated using maximum likelihood estimation (MLE). The Heckman correction for selection is also addressed. EPPS 6316 or the equivalent recommended. (3-0) Y

EPPS 7368 Spatial Epidemiology (3 semester hours) Examines the conceptual and analytic tools used to understand how spatial distributions of exposure impact on processes and patterns of disease. Emphasizes the special design, measurement, and analysis issues associated with spatial patterns of diseases. Contemporary diseases of public health importance are addressed, and the statistical and inferential skills are provided that can be used in understanding how spatial patterns arise and their implications for intervention. Prerequisite: EPPS 6313 or equivalent. (3-0) R
EPPS 7370 Time Series Analysis (3 semester hours) The course considers several important topics in applied time series analysis including the specification and testing Box-Jenkins transfer function/intervention models. Other topics include pooled cross-sectional time series models, VAR, the LSE Approach, unit-roots, cointegration, error correction models, encompassing and exogeneity tests, and ARFIMA models. Students also learn how to use programs such as Eviews and RATS. EPPS 7316 or equivalent recommended (3-0) R
EPPS 7380 Applied Multivariate Analysis (3 semester hours) Application of multivariate statistical techniques to spatial and economic data. Covers parametric and non-parametric statistical theory and application including multiple linear and non-linear regression, poisson, and binomial regression, principal components and factor analysis, discriminant function analysis, and canonical correlation. Includes an introduction to SAS computing. Prerequisites: EPPS 6316 or ECON 6306 (3-0) R
EPPS 7386 Survey Research (3 semester hours) This course exposes students to the use of survey methods in social science research. Emphasis is placed on interview and questionnaire techniques and the construction and sequencing of survey questions. Attention is also devoted to sampling theory, sampling and non-sampling errors, and the use of recent advances in fieldwork to reduce measurement error in surveys. EPPS 6313 or equivalent recommended. (3-0) R
EPPS 7388 Workshop in Teaching Effectiveness (1-3 credit hours) Workshop will focus on preparing students for positions as teaching assistants, lecturers, and those who expect to teach as a career in the Social Sciences. Emphasis will be placed on videotaped student presentations and feedback, guest presentations, student visits to EPPS faculty classes. [(1-3)-0] R.


Last Updated: August 10, 2010