AASP African American Studies
AASP303 Computer Applications in African American Studies
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: STAT100 or SOCY201 or MATH111 or equivalent. Introduction to statistics and database processing software used in model estimation and simulation in policy analysis. Special emphasis on applications for applied research on policy problems confronting minority communities.
Keywords: Analytic Software, Model Estimation, Simulation, Subject-specific Statistical Techniques
ANTH Anthropology
ANTH630 Quantification and Statistics in Applied Anthropology
(3 credits) Grade Method: REG/AUD.
An intensive overview of key quantitative and statistical approaches used by social scientists in applied ad policy research. This includes nonparametric and parametric statistical approaches. Students utilize statistical software and analyze existing and student-created databases. Anthropological case studies are emphasized.
Keywords: Analytic Software, Subject-specific Statistical Techniques
CCJS Criminology and Criminal Justice
CCJS200 (PermReq) Statistics for Criminology and Criminal Justice
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisites: CCJS100 or CCJS105, and MATH111 with a grade of C or higher. Introduction to descriptive and inferential statistics, graphical techniques, and the computer analysis of criminology and criminal justice data. Basic procedures of hypothesis testing, correlation and regression analysis, and the analysis of continuous and binary dependent variables. Emphasis upon the examination of research problems and issues in criminology and criminal justice.
Keywords: Analytic Software, Correlation, Graphical Techniques, Hypothesis Testing, Regression, Subject-specific Statistical Techniques
CCJS604 (PermReq) Policy Analysis Project
(3 credits) Grade Method: REG. Individual Instruction course: contact department or instructor to obtain section number.
An application of statistical and conceptual tools to criminal justice data in the student's area of concentration, resulting in a paper reporting the conceptualization, analytic methods and results. The topic of the independent study will be chosen through individual consultation with the instructor.
Keywords: Subject-specific Statistical Techniques
CCJS611 Statistical Tools for Criminal Justice
(3 credits) Grade Method: REG.
An introduction to essential statistical concepts for analyzing crime and evaluating criminal justice policies. Interpreting crime trends and correlations, risk and conditional probability analysis for repeat offenders and hot spots of crime, time series analysis, experimental statistics, effect sizes, statistical power and significance.
Keywords: Correlation, Experimental Design/Statistics, Hypothesis Testing, Probability/Stat Theory, Risk Analyses, Time Series
CCJS612 Applied Data Analysis in Criminal Justice
(3 credits) Grade Method: REG/AUD.
Requires students to analyze such data as patterns and distributions of criminal careers, temporal and spatial data on reported crimes, recidivism rates after correctional programs, and statistical profiles of offender M.O. patterns. Data base management, computerized crime mapping, graphical and tabular methods for displaying data.
Keywords: Graphical Techniques
CCJS710 Advanced Research Methods in Criminology
(3 credits) Grade Method: REG/AUD.
Prerequisite: approved doctoral level statistics course. Formerly CRIM 710. Application of advanced research methods and data analysis strategies to criminological and criminal justice problems.
Keywords: Research Methods, Subject-specific Statistical Techniques
ECON Economics
ECON321 Economic Statistics
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: ECON200, ECON201, {MATH220 or MATH140} with a grade of 'C'(2.0) or better. For ECON majors only. Not open to students who have completed BMGT230 (unless with department permission) or BMGT231. Credit will be granted for only one of the following: BMGT230, BMGT231 or ECON321. Introduction to the use of statistics in economics. Topics include: Probability, random variables and their distributions, sampling theory, estimation, hypothesis testing, analysis of variance, regression analysis and correlation.
Keywords: Correlation, Hypothesis Testing, Probability/Stat Theory, Regression
ECON414 Game Theory
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: ECON326 with a grade of 'C' or better (or ECON306 by permission of department). For ECON majors only. Not open to students who have completed GVPT399A. Credit will be granted for only one of the following: ECON414 or GVPT399A. Studies the competitive and cooperative behavior that results when several parties with conflicting interests must work together. Learn how to use game theory to analyze situations of potential conflict. Applications are drawn from economics, business, and political science.
Keywords: Game Theory
ECON422 Econometrics I
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisites: ECON321 (or STAT400) with a grade of 'C' (2.0) or better. For ECON majors only. Emphasizes the interaction between economic problems and the assumptions employed in statistical theory. Formulation, estimation, and testing of economic models, including single variable and multiple variable regression techniques, theory of identification, and issues relating to inference.
Keywords: Regression
ECON423 Econometrics II
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: ECON422. For ECON majors only. Interaction between economic problems and specification and estimation of econometric models. Topics include issues of autocorrelation, heteroscedasticity, functional form, simultaneous equation models, and qualitative choice models.
Keywords: Regression
ECON424 Computer Methods in Economics
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: ECON325 and ECON326 (or ECON305 and ECON306 by permission of department) and ECON321 with a grade of 'C' (2.0) or better. For ECON majors only. Database development from Internet and other sources, research methods, and statistical analysis in economics using EXCEL and SAS.
Keywords: Analytic Software, Research Methods
ECON621 Quantitative Methods I
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 600 or permission of department. An introduction to econometrics, and a development of the mathematical background concepts needed. Background materials relate to various topics in linear algebra, and in distribution theory. Focus on estimation, hypothesis testing, and prediction in the classical linear regression model. Corresponding large sample issues are considered. Special topics such as non-nested models, hypotheses relating to nonlinear functions of parameters, and specification analysis, including tests for the dynamic stability of a model.
Keywords: Correlation, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Regression, Structural Equation Models
ECON622 Quantitative Methods II
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 621 or permission of department. A continuation of ECON 621. Topics relate to the generalized least squares model, to dynamic single equation and simultaneous equation models, and to qualitative dependent variable models. Among the topics discussed are various tests for heteroskedasticity and autocorrelation, prediction issues, time series models such as ARCH and GARCH models, tests for unit roots, panel data models, and systems estimation including the GMM procedure. Both linear and nonlinear models are considered. General testing principles, such as likelihood ratio, Wald, and Hausman-type test are also discussed.
Keywords: Correlation, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Panel Data Models, Qualitative & Limited Dependent Variable Models, Regression, Spatial Statistics, Structural Equation Models, Time Series
ECON623 Econometrics I
(3 credits) Grade Method: REG/AUD.
Introduction to and development of aspects of mathematical statistics relevant for econometrics. Topics include: probability measure, random variables, density functions and distribution functions, expectations, moment generating functions, conditional distributions, independence, parameter estimators, hypothesis testing, sufficient statistics.
Keywords: Correlation, Hypothesis Testing, Probability/Stat Theory
ECON624 Econometrics II
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 623 or permission of department. Estimation, hypothesis testing and prediction in the classical and generalized linear regression model. Topics include: ordinary least squares and generalized least squares, including a discussion of their algebraic, small and large sample properties, prediction and parameter restriction; specification tests; large sample distribution theory.
Keywords: Correlation, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Regression
ECON625 Computational Economics
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 604 and ECON 622; or ECON 721. Credit will be granted for only one of the following: ECON 625 or ECON 698R. Formerly ECON 698R. A one-semester course designed to give students tools for numerical dynamic programming and computation of related general equilibrium and game-theoretic problems.
Keywords: Game Theory, Statistical Programming
ECON626 Empirical Microeconomics
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 622 or ECON 721 or permission of instructor. Empirical techniques that are particularly valuable in the analysis of microeconomic data. Topics include panel data, nonlinear optimization, limited dependent variables, truncated, censored, and selected samples, the analysis of natural experiments, and quantile regressions. For ECON majors only.
Keywords: Panel Data Models, Qualitative & Limited Dependent Variable Models, Regression, Subject-specific Statistical Techniques
ECON627 Empirical Macroeconomics
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 622 or ECON 721 or permission of instructor. Introduction to the solution, identification, estimation, and evaluation of macroeconomic models under rational expectations. Emphasis is on those tools that allow researchers to tightly link economic theory with econometric methods. Hands-on application of these techniques to empirical macroeconomic problems (business cycles, growth, consumption/ saving, investment), using time-series and panel data.
Keywords: Regression, Subject-specific Statistical Techniques, Time Series
ECON721 Econometrics III
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 624 or permission of instructor. A continuation of ECON 624. Estimation hypothesis testing and prediction in various generalized linear regression models, and in dynamic and simultaneous equation models. Topics include: autocorrelation, heteroskedasticity, seemingly unrelated regressions, cross section and time-series models, and general testing principles for significance.
Keywords: Correlation, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Panel Data Models, Regression, Stochastic Process, Structural Equation Models, Time Series
ECON722 Econometrics IV
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 721 or permission of instructor. A continuation of ECON 721. A "topics course." The topics considered are a large subset of the following: inference in parametric and semi-parametric nonlinear econometric models (least mean distance and GMM estimation); pretest estimation issues; rational expectations models; further issues in specification testing; qualitative and limited dependent variable models (binary and polychotomous choice models, truncated and censored samples, etc.); causality and exogeneity; time series models with unit roots; cointegration; spatial models; ARCH and GARCH models; the Kalman filter; cross section time series models (random parameters); and optimal control.
Keywords: Analytic Software, Bayesian, Correlation, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Nonparametric Methods, Qualitative & Limited Dependent Variable Models, Regression, Spatial Statistics, Stochastic Process, Structural Equation Models, Time Series
ECON723 Time Series Econometrics
(3 credits) Grade Method: REG.
Prerequisite: ECON 622 or ECON 722 or permission of instructor. Provides a broad survey of the models and methods commonly used in the analysis of time series data. Emphasis on analyzing the statistical properties of the methods being discussed. Particular attention to recent developments in time series econometrics.
Keywords: Bayesian, Hypothesis Testing, Large Sample Theory, Model Estimation, Multivariate Estimation, Regression, Time Series
ECON725 Empirical Economic Modeling I
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 622 or ECON 721. Credit will be granted for only one of the following: ECON 725 or ECON 625. The experience of building a structural macroeconomic model. Computer techniques for creating models and writing model-building software. Basics of input-output economics.
Keywords: Analytic Software, Statistical Programming
ECON726 Empirical Economic Modeling II
(3 credits) Grade Method: REG/AUD.
Prerequisite: ECON 725. Modeling of interindustry flows, personal consumption and saving, investment, exports and imports, wages, employment, profits, prices, interest and income distribution. Analyzing a model's simulation properties. Applications of general models to specific questions.
Keywords: Regression, Simulation
GEOG Geography
GEOG605 Quantitative Spatial Analysis
(3 credits) Grade Method: REG/AUD.
Prerequisite: GEOG 305; or permission of department. Multivariate statistical method applications to spatial problems. Linear and non-linear correlation and regression, factor analysis, cluster analysis. Spatial statistics including: trend surfaces, sequences, point distributions. Applications orientation. There is a $40.00 lab fee for this course.
Keywords: Factor Analysis / LC, Regression, Spatial Statistics
GEOG606 Quantitative Spatial Analysis
(3 credits) Grade Method: REG/AUD.
Prerequisite: GEOG 305; or permission of department. Credit will be granted for only one of the following: GEOG 605 or GEOG 606. Formerly GEOG605. Multivariate statistical method applications to spatial problems. Linear and non-linear correlation and regression, factor analysis, cluster analysis. Spatial statistics including: trend surfaces, sequences, point distributions. Applications orientation. The course has a $40 lab fee.
Keywords: Factor Analysis / LC, Regression, Spatial Statistics
GVPT Government and Politics
GVPT227 The Craft of Political Science Research
(4 credits) Grade Method: REG.
Prerequisite: GVPT 170; GVPT 100. Sophomore standing. For BSOS majors only. An introduction to research design and statistics applicable to Political Science.
Keywords: Subject-specific Statistical Techniques
GVPT622 Quantitative Methods For Political Science
(3 credits) Grade Method: REG/AUD.
Introduction to quantitiative methods of data analysis, with emphasis on statistical methods and computer usage. Measures of association, probability, correlation, linear regression estimation techniques, introductory analysis of variance, and use of package computer programs. Course will meet in the LeFrak OASIS lab.
Keywords: Analysis of Variance, Analytic Software, Correlation, Probability/Stat Theory, Regression
GVPT729A Special Topics in Quantitative Political Analysis: Advanced MLE
(3 credits) Grade Method: REG/AUD.
Prerequisite: GVPT622 and GVPT722.
Keywords: Research Methods
HESP Hearing and Speech Sciences
HESP724 Research Design
(3 credits) Grade Method: REG/AUD.
Prerequisite: a course in basic statistics. Evaluations of research designs, critique of published articles and student involvement in designing experiments on assigned topics.
Keywords: Experimental Design/Statistics
PSYC Psychology
PSYC200 Statistical Methods in Psychology
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: PSYC100; and (MATH111 or MATH140 or MATH220) with a C (2.0) or higher. A basic introduction to quantitative methods used in psychological research. Restricted to PSYC and BSCI majors. All other majors require permission in BPS 1107.
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Keywords: Hypothesis Testing, Large Sample Theory, Probability/Stat Theory
PSYC601 Quantitative Methods I
(4 credits) Grade Method: REG/AUD.
Prerequisite: PSYC 200 or equivalent. A basic course in quantitative/mathematical analysis and statistical methods in psychology with an emphasis on conceptual understanding. Topics include issues in measurement, probability theory, statistical inference and hypothesis testing, parameter estimation, bivariate regression, and correlation. For PSYC majors only. For all non-psychology graduate students, written permission of the instructor and department is required.
Keywords: Experimental Design/Statistics, Hypothesis Testing, Regression
PSYC602 Quantitative Methods II
(4 credits) Grade Method: REG/AUD.
Prerequisite: PSYC 601. A continuation of PSYC 601. Topics include experimental design, analysis of variance, analysis of covariance, multiple regression, and general linear models. For all non-psychology graduate students, written permission of the instructor is required.
Keywords: Analysis of Variance, Experimental Design/Statistics, Regression
PSYC701 Multivariate Analysis I
(3 credits) Grade Method: REG/AUD.
Prerequisite: PSYC 602 or permission of instructor. Fundamentals of maxtrix algebra, multivariate distributions, multivariate estimation problems and test of hypotheses, general linear model.
Keywords: Hypothesis Testing, Multivariate Estimation, Regression
PSYC702 Multivariate Analysis II
(3 credits) Grade Method: REG/AUD.
Prerequisite: PSYC 701 or permission of instructor. Component and factor analysis with emphasis on the appropriateness of the models to psychological data. Both theoretical issues and research implications will be discussed. The course will treat the factor analytic model, the three indeterminant problems of communalities, factor loadings, and factor scores, extraction algorithms, rotational algorithms, and the principal component model. For all non-psychology graduate students, written permission of the instructor is required.
Keywords: Factor Analysis / LC, Multivariate Estimation
SOCY Sociology
SOCY201 (PermReq) Introductory Statistics for Sociology
(4 credits) Grade Method: REG/P-F/AUD.
Prerequisite: SOCY100 and MATH111 or equivalent. Not open to students who have completed BMGT231, ENEE324, or STAT400. Credit will be granted for only one of the following: AREC484, BIOM301, BMGT230, CNEC400, ECON321, EDMS451, GEOG305, GVPT422, PSYC200, SOCY201, URSP350, or TEXT400. Elementary descriptive and inferential statistics. Construction and percentaging of bivariate contingency tables; frequency distributions and graphic presentations; measures of central tendency and dispersion; parametric and nonparametric measures of association and correlation; regression; probability; hypothesis testing; the normal, binomial and chi-square distributions; point and interval estimates.
Keywords: Correlation, Graphical Techniques, Hypothesis Testing, Probability/Stat Theory, Regression
SOCY601 Statistics For Sociological Research I
(3 credits) Grade Method: REG/AUD.
Prerequisite: SOCY 201 or equivalent, and permission of instructor or graduate director. Credit will be granted for only one of the following: SOCY 601 and SURV 601. Introductory statistical concepts are covered including descriptive statistics, probability, sampling distributions, expected values, hypothesis testing, tests of significance, measures of association, and if time permits, introduction to regression analysis. Statistical programming software may be used. Also offered as SURV 601.
Keywords: Analytic Software, Correlation, Hypothesis Testing, Probability/Stat Theory, Regression, Statistical Programming
SOCY602 Statistics For Sociological Research II
(3 credits) Grade Method: REG/AUD.
Prerequisite: SOCY 601 or equivalent, and permission of instructor or graduate director. Credit will be granted for only one of the following: SOCY 602 or SURV 602. This course introduces regression analysis using matrix algebra. Topics include bivariate regression, multivariate regression, tests of significance, regression diagnostics, indicator variables, interaction terms, extra sum of squares, and the general linear model. Other topics may be addressed such as logistic regression and path analysis. Statistical programming software may be used.
Keywords: Analytic Software, Factor Analysis / LC, Hypothesis Testing, Regression, Statistical Programming
SOCY604 Survey Research Methods
(3 credits) Grade Method: REG/AUD.
The design, collection, and analysis of data using the method of the social survey. Comparison of the advantages and disadvantages of the survey method with those of other methods of social inquiry. Control over the major sources of survey variation: survey mode, sampling, questionnaire format, question wording, interviewing and coding. Measurement and multivariate analysis alternatives.
Keywords: Research Methods, Survey Sampling
SOCY605 Methods of Program Evaluation
(3 credits) Grade Method: REG/AUD.
Prerequisite: SOCY 202 or equivalent or permission of instructor. Survey of research methods used to evaluate social programs. Conceptualization and measurement of program inputs and outcomes; experimental, quasi-experimental and time-series designs for determining causal influence of program; strategies of data analysis.
Keywords: Experimental Design/Statistics, Research Methods, Time Series
SOCY609 Practicum in Social Research
(3 credits) Grade Method: REG/AUD.
Keywords: Research Methods, Statistical Programming
SOCY709 Advanced Special Topics in Data Analysis: Categorical Analysis
(3 credits) Grade Method: REG/AUD.
Keywords: Content Analysis, Factor Analysis / LC, Regression
SURV Survey Methodology
SURV400 Fundamentals of Survey Methodology
(3 credits) Grade Method: REG.
Prerequisite: STAT100 or permission of department. Credit will be granted for only one of the following: SURV699M or SURV400. Formerly SURV699M. Introduces the student to a set of principles of survey design that are the basis of standard practices in the field. The course exposes the student to both observational and experimental methods to test key hypotheses about the nature of human behavior that affect the quality of survey data. It will also present important statistical concepts and techniques in simple design, execution, and estimation, as well as models of behavior describing errors in responding to survey questions. Not acceptable to graduate degrees in SURV.
Keywords: Experimental Design/Statistics, Hypothesis Testing, Survey Sampling
SURV410 Introduction to Probability Theory
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: MATH240; and MATH241 or permission of department. Also offered as STAT410. Credit will be granted for only one of the following: SURV410 or STAT410. Probability and its properties. Random variables and distribution functions in one and several dimensions. Moments, characteristic functions, and limit theorems.
Keywords: Probability/Stat Theory
SURV420 Introduction to Statistics
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: SURV410 or STAT410. Also offered as STAT420. Credit will be granted for only one of the following: STAT420 or SURV420. Mathematical statistics, presenting point estimation, sufficiency, completeness, Cramer-Rao inequality, maximum likelihood, confidence intervals for parameters of normal distributions, chi-square tests, analysis of variance, regression, correlation, and nonparametric methods. Course is offered in the spring semester only.
Keywords: Analysis of Variance, Correlation, Nonparametric Methods, Probability/Stat Theory, Regression
SURV440 Sampling Theory
(3 credits) Grade Method: REG/P-F/AUD.
Prerequisite: STAT401 or STAT420. Not open to students who have completed STAT440. Simple random sampling, sampling for proportions, estimation of sample size, sampling with varying probabilities of selection, stratification, systematic selection, cluster sampling, double sampling, and sequential sampling. Also offered as STAT 440.
Keywords: Correlation, Probability/Stat Theory, Survey Sampling
SURV601 Social Statistics I
(3 credits) Grade Method: REG/AUD.
Prerequisite: SOCY 401 or permission of instructor. Not open to students who have completed SOCY 601. Probability, hypothesis testing, the normal, chi-square and t-distributions, correlation, and simple analysis of variance. Emphasis is on applications of statistics. Students complete data analytic exercises using real data. Also offered as SOCY 601.
Keywords: Analysis of Variance, Correlation, Hypothesis Testing
SURV602 Social Statistics II
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 601 or permission of department. Not open to SOCY students who have completed SOCY 602. Credit will be granted for only one of the following: SURV 602 or SOCY 602. Statistical analyses based on the general linear model. Topics include simple regression, multiple regression, with an emphasis on diagnostic procedures checking model assumptions; elementary structural equation models; and logistic regression. Emphasis on applications of these analytic procedures to real data.
Keywords: Regression
SURV615 Statistical Methods I
(3 credits) Grade Method: REG/AUD.
Prerequisite: two course sequence in probability and statistics or equivalent. First course in a two term sequence in applied statistical methods covering topics such as regression, analysis of variance, categorical data, and survival analysis. This course begins on 09/06/06. It runs concurrently with the University of Michigan course.
Keywords: Analysis of Variance, Hypothesis Testing, Regression
SURV616 Statistical Methods II
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 615. Builds on the introduction to linear models and data analysis provided in Statistical Methods I. Topics include analysis of longitudinal data and time series, categorical data analysis and contingency tables, logistic regression, log-linear models for counts, statistical methods in epidemiology, and introductory life testing.
Keywords: Factor Analysis / LC, Regression
SURV620 (PermReq) Survey Practicum I
(3 credits) Grade Method: REG/AUD.
Prerequisite: degree seeking student in JPSM or permission of instructor. First part of an applied workshop in sample survey design, implementation, and analysis. Problems of moving from substantive concepts to questions on a survey questionnaire, designing a sample, pretesting the questionnaire, administering the questionnaire to a sample, processing and editing the data, and analyzing the results.
Keywords: Statistical Programming, Survey Sampling
SURV621 Survey Practicum II
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 620. Second part of an applied workshop in sample survey design, implementation, and analysis. Problems of moving from substantive concepts to questions on a survey questionnaire, designing a sample, pretesting the questionnaire, administering the questionnaire to a sample, processing and editing the data, and analyzing the results.
Keywords: Statistical Programming, Survey Sampling
SURV623 Data Collection Methods in Survey Research
(3 credits) Grade Method: REG/AUD.
Review of alternative data collection methods used in surveys, concentrating on the impact these techniques have on the quality of survey data, including measurement error properties, levels of nonresponse and coverage error. Reviews of the literature on major mode comparisons (face-to-face interviewing, telephone survey and self-administered questionnaires), and alternative collection methods (diaries, administrative records, direct observation, etc.). The statistical and social science literatures on interviewer effects and nonresponse, and current advances in computer-assisted telephone interviewing (CATI), computer-assisted personal interviewing (CAPI), and other methods such as touchtone data entry (TDE) and voice recognition (VRE). This course begins on 09/11/06. It runs concurrently with the University of Michigan course.
SURV625 Applied Sampling
(3 credits) Grade Method: REG/AUD.
Prerequisite: statistics course approved by the department. Practical aspects of sample design. Topics include: probability sampling (including simple random, systematic, stratified, clustered, multistage and two-phase sampling methods), sampling with probabilities proportional to size, area sampling, telephone sampling, ratio estimation, sampling error estimation, frame problems, nonresponse, and cost factors. This coure will be held at BLS Conference Center, Meeting Room 9, Washington DC.
Keywords: Survey Sampling
SURV699 Special Topics in Survey Methodology: Readings in Survey Methodology
(1-4 credits) Grade Method: REG/AUD.
Keywords: Analysis of Variance, Analytic Software, Bayesian, Experimental Design/Statistics, Hypothesis Testing, Large Sample Theory, Model Estimation, Nonparametric Methods, Probability/Stat Theory, Regression, Research Methods, Statistical Programming, Subject-specific Statistical Techniques, Survey Sampling
SURV699A Special Topics in Survey Methodology: Categorical Data Analysis
(3 credits) Grade Method: REG/AUD.
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Keywords: Correlation, Hypothesis Testing, Probability/Stat Theory, Survey Sampling
SURV699C Special Topics in Survey Methodology: Introduction to Questionnaire Design
(1 credit) Grade Method: REG/AUD.
Keywords: Bayesian, Hypothesis Testing, Regression
SURV699K Special Topics in Survey Methodology: Multi-Level Analysis of Survey Data
(3 credits) Grade Method: REG/AUD.
Keywords: Analytic Software
SURV699M Special Topics in Survey Methodology: Measurement Error Methods
(1-4 credits) Grade Method: REG/AUD.
Keywords: Analytic Software, Large Sample Theory, Regression
SURV699N Special Topics in Survey Methodology: Introduction to Survey Statistics Using Compusters
(3 credits) Grade Method: REG/AUD.
Keywords: Analytic Software, Statistical Programming
SURV699S Special Topics in Survey Methodology: Prediction Approach to Sampling Theory
(3 credits) Grade Method: REG/AUD.
Prerequisite: STAT 420, SURV 440, OR EQUIVALENTS.
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Keywords: Graphical Techniques, Regression, Simulation, Survey Sampling
SURV701 Analysis of Complex Sample Data
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 625. Analysis of data from complex sample designs covers: the development and handling of selection and other compensatory weights; methods for handling missing data; the effect of stratification and clustering on estimation and inference; alternative variance estimation procedures; methods for incorporating weights, stratification and clustering, and imputed values in estimation and inference procedures for complex sample survey data; and generalized design effects and variance functions. Computer software that takes account of complex sample design in estimation. This course begins on 09/07/06. It runs concurrently with the University of Michigan course.
Keywords: Analytic Software, Survey Sampling
SURV722 Randomized/Nonrandomized Design
(3 credits) Grade Method: REG/AUD.
Research designs from which causal inferences are sought. Classical experimental design will be contrasted with quasi-experiments, evaluation studies, and other observational study designs. Emphasis placed on how design features impact the nature of statistical estimation and inference from the designs. Issues of blocking, balancing, repeated measures, control strategies, etc.
Keywords: Experimental Design/Statistics
SURV723 (PermReq) Total Survey Error
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 625. Total error structure of sample survey data, reviewing current research findings on the magnitudes of different error sources, design features that affect their magnitudes, and interrelationships among the errors. Coverage, nonresponse, sampling, measurement, and postsurvey processing errors. For each error source reviewed, social science theories about its causes and statistical models estimating the error source are described. Empirical studies from the survey methodological literature are reviewed to illustrate the relative magnitudes of error in different designs. Emphasis on aspects of the survey design necessary to estimate different error sources. Relationships to show how attempts to control one error source may increase another source. Attempts to model total survey error will be presented.
Keywords: Survey Sampling
SURV742 Inference from Complex Surveys
(3 credits) Grade Method: REG/AUD.
Prerequisite: STAT 440. Inference from complex sample survey data covering the theoretical and empirical properties of various variance estimation strategies (e.g., Taylor series approximation, replicated methods, and bootstrap methods for complex sample designs). Incorporation of those methods into inference for complex sample survey data. Variance estimation procedures applied to descriptive estimators and to analysis of categorical data. Generalized variances and design effects presented. Methods of model-based inference for complex sample surveys examined, and results contrasted to the design-based type of inference used as the standard in the course. Real survey data illustrating the methods discussed. Students will learn the use of computer software that takes account of the sample design in estimation.
Keywords: Analysis of Variance, Analytic Software, Regression, Survey Sampling
SURV744 Topics in Sampling
(3 credits) Grade Method: REG/AUD.
Prerequisite: SURV 440. Advanced course in survey sampling theory.
Keywords: Small Area Estimation, Survey Sampling
SURV798B Advanced Topics in Survey Methodology: Small Area Estimation
(3 credits) Grade Method: REG/AUD.
Also offered as STAT798B.
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Keywords: Analytic Software, Regression, Small Area Estimation
SURV798B Advanced Topics in Survey Methodology: Small Area Estimation
(3 credits) Grade Method: REG/AUD.
Also offered as STAT798B.
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Keywords: Bayesian