Course Information

General Information

**For course enrollment problems please e-mail higgvt@vt.edu

Course Duplications | Computer Literacy | Course Projects

Courses Offered

Undergraduate Courses | Graduate Courses | Syllabi


Course Duplications:

No credit will be given for more than one course in each of the following groups (in parentheses) of partially duplicated courses: (3005, 3615, 4604). (3006, 3616, 4604, 4706). (4105, 4705, 4714, 4724). No credit will be given for: 2004 if taken with or after any other statistics course; 2404 if taken with or after any of 3104, 4105, 4705, 4714, 4724; 3604 if taken with or after any statistics course except 2004, 2404, 3104. MSci 2405 may not be used as a substitute for credit as a statistics course. Exceptions to this rule may be granted if the student was officially registered as a Business major at the time MSci 2405 was taken.

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Computer Literacy:

Many statistics courses involve the use of statistical software; primarily MINITAB or SAS. Experience with the software is not expected, but students should have familiarity with either the Windows or MacIntosh operating system and access to a computer. These courses are specified by "WIN/MAC" under prerequisites.

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Course Projects:

 

Many of the upper-division course descriptions below include the word "Project." Those courses will usually include a major term project, either individually or in small groups. These projects are designed to give students the kind of insight and experience in realistic statistical practice that cannot be obtained in classroom lectures or short-term homework assignments.

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Undergraduate Statistics Courses (STAT)

  • 2004: Introductory Statistics
  • 2954: Intro to Data Management and SAS
  • 2964: Field Study
  • 3005-3006: Statistical Methods
  • 3504: Nonparametric Statistics
  • 3604: Statistics for the Social Sciences
  • 3615-3616: Biological Statistics
     
  • 3704:Statistics for Engineering Applications
  • 4004: Methods of Statistical Computing
  • 4024: Consulting
  • 4105-4106: Theoretical Statistics
  • 4204: Experimental Designs
  • 4214: Methods of Regression Analysis
  • 4504: Applied Multivariate Analysis
  • 4514: Contingency Table Analysis
  • 4524: Sample Survey Methods
  • 4534: Applied Statistical Time Series Analysis
  • 4604: Statistical Methods for Engineers
  • 4705-4706: Probability and Statistics for Engineers
  • 4714: Probability and Statistics for Electrical Engineers
  • 4724: Statistical Theory for Economists
  • 4804 (AAEC 4804): Elementary Econometrics
  • 4974: Independent Study
  • 4984: Special Study
  • 4994: Undergraduate Research
     
  • Advanced Undergraduate Courses
  • Link to all undergraduate course syllabi

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    2004: INTRODUCTORY STATISTICS

    Fundamental concepts and methods of statistics with emphasis on interpretation of statistical arguments. An introduction to design of experiments, data analysis, correlation and regression, concepts of probability theory, sampling errors, confidence intervals, and hypothesis tests. See also Course Duplications. Pre: MATH 1015. (4H,3C). I,II,III,IV.

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    2954: INTRODUCTION TO DATA MANAGEMENT AND SAS

    Introduction to computer workstations, Unix command language, common desktop environment. Computer networking concepts. Data management and presentation in the Statistical Analysis System (SAS), including data input, data manipulation, graphs, and macros. Co: 3005 (1H, 2L, 2C).

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    2964: FIELD STUDY

    Pass/fail only. Variable credit course.

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    3005-3006: STATISTICAL METHODS

    3005:: Basic statistical methodology: exploratory data techniques, estimation, inference, comparative analysis by parametric, nonparametric, and robust procedures. Analysis of variance (one-way), multiple comparisons, and categorical data.

    3006: Analysis of variance, simple and multiple, linear and nonlinear regression, analysis of covariance. Use of MINITAB.
    Pre: MATH 1206 and WIN/MAC. (3H,3C). 3005: I,II,III; 3006: I,II,IV.

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    3504: NONPARAMETRIC STATISTICS

    Statistical methodology based on ranks, empirical distributions, and runs. One and two sample tests, ANOVA, correlation, goodness of fit, and rank regression, R-estimates and confidence intervals. Comparisons with classical parametric methods. Emphasis on assumptions and interpretation. Pre: WIN/MAC and one of 3006, 4106, 4604, 4706. (3H,3C). I. Even years.

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    3604: STATISTICS FOR THE SOCIAL SCIENCES

    Statistical methods for nominal, ordinal, and interval levels of measurement. Topics include descriptive statistics, elements of probability, discrete and continuous distributions, one and two sample tests, measures of association. Emphasis on comparison of methods and interpretations at different measurement levels. See also Course Duplications. Pre: MATH 1015. (3H,3C). I,II,IV.

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    3615-3616: BIOLOGICAL STATISTICS

    Descriptive and inferential statistics in a biological context.
    3615: Fundamental principles, one- and two-sample parametric inference, simple linear regression, frequency data.
    3616: One- and two-way ANOVA, multiple regression, correlation, nonparametrics, using the MINITAB computer package.
    Pre: WIN/MAC for 3616. (3H,3C). 3615: I,II,III; 3616: II, IV.

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    3704: STATISTICS FOR ENGINEERING APPLICATIONS

    Introduction to statistical methodology with emphasis on engineering experimentation: probability distributions, estimation, hypothesis testing, regression, and analysis of variance. Only one of the courses 3704, 4604, 4705, and 4714 may be taken for credit. Pre: MATH 2224. (2H,2C) I,II.

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    4004: METHODS OF STATISTICAL COMPUTING

    Computationally intensive computer methods used in statistical analyses. Statistical univariate and multivariate graphics; resampling methods including bootstrap estimation and hypothesis testing and simulations; classification and regression trees; scatter plot smoothing and splines. Pre: 4105, 4214. (4H,3C)

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    4024: COMMUNICATION SKILLS FOR STATISTICAL CONSULTING

    Specialized tools for design and analysis applicable to current interdisciplinary statistical consulting projects. Oral and written communication skills important to effective client-statistician interactions, including interview, report-writing, and oral presentation skills. Pre: 3006, 4204. (2H,2C)

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    4105-4106: THEORETICAL STATISTICS

    4105: Probability theory, counting techniques, conditional probability; random variables, moments; moment generating functions; multivariate distributions; transformations of random variables; order statistics.
    4106: Convergence of sequences of random variables; central limit theorem; methods of estimation; hypothesis testing; linear models; analysis of variance.
    Pre: MATH 2224. (3H,3C). 4105: I; 4106: II.

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    4204: EXPERIMENTAL DESIGNS

    Fundamental principles of designing and analyzing experiments with application to problems in various subject matter areas. Discussion of completely randomized, randomized complete block, and latin square designs, analysis of covariance, split--plot designs, factorial and fractional designs, incomplete block designs. Project. Pre: WIN/MAC and one of 3006, 3616, 4106, 4706, 5605, 5615. (3H,3C). I.

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    4214: METHODS OF REGRESSION ANALYSIS

    Multiple regression including variable selection procedures; detection and effects of multicollinearity; identification and effects of influential observations; residual analysis; use of transformations. Non-linear regression, the use of indicator variables, and logistic regression. Use of SAS. Project. Pre: WIN/MAC and one of 3006, 3616, 4106, 4706, 5606 or 5616. (3H,3C). I.

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    4444: APPLIED BAYESIAN STATISTICS

    Introduction to Bayesian methodology with emphasis on applied statistical problems: data displaying, prior distribution elicitation, posterior analysis, models for proportions, means and regression. Pre: MATH 2224. (3H,3C)

    4504: APPLIED MULTIVARIATE ANALYSIS

    Non-mathematical study of multivariate analysis. Multivariate analogs of univariate test and estimation procedures. Simultaneous inference procedures. Multivariate analysis of variance, repeated measures, inference for dispersion and association parameters, principal components analysis, discriminant analysis, cluster analysis. Use of SAS. Project. Pre: WIN/MAC and one of 3006, 4706, 5606, 5616. (3H,3C). Even years.

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    4514: CONTINGENCY TABLE ANALYSIS

    Statistical techniques for frequency data. Goodness-of-fit. Tests and measures of association for two-way tables. Log-linear models for multidimensional tables. Parameter estimation, model selection, incomplete tables, ordinal categories, logistic regression. Use of BMDP and SPSSx. Project. Pre: WIN/MAC and one of 3006, 3616, 4106, 4706, 5606, 5616. (3H,3C). II. Even years.

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    4524: SAMPLE SURVEY METHODS

    Statistical methods for the design and analysis of survey sampling. Fundamental survey designs. Methods of randomization specific to various survey designs. Estimation of population means, proportions, totals, variances, and mean squared errors. Design of questionnaires and organization of a survey. Project. Pre: One of 3006, 3616, 4106, 4706, 5606, 5616. (3H,3C). I. Odd years.

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    4534: APPLIED STATISTICAL TIME SERIES ANALYSIS

    An applied course in time series analysis. A uniform coverage of both time domain and frequency domain methods that are used in the physical, biological, and social sciences and by applied statisticians. Pre: One of 3006, 4106, 4706, 4714, 5606, 5616; WIN/MAC, Math 1206. (3H,3C). II. Odd years.

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    4604: STATISTICAL METHODS FOR ENGINEERS

    Introduction to statistical methodology with emphasis on engineering applications: probability distributions, estimation, hypothesis testing, regression, analysis of variance, quality control. Only one of the courses 4604, 4705, and 4714 may be taken for credit. Pre: MATH 1206 and WIN/MAC. (3H,3C). I,II.

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    4705-4706: PROBABILITY AND STATISTICS FOR ENGINEERS

    Basic concepts of probability and statistics with emphasis on engineering applications.
    4705: Probability, random variables, distribution theory, sampling distributions, estimation, hypothesis testing.
    4706: Hypothesis testing, simple and multiple regression, analysis of variance, factorial experiments. Only one of the courses 4604, 4705, and 4714 may be taken for credit.
    Pre: MATH 2224 and WIN/MAC. (3H,3C). 4705: I,II,III; 4706: I,II.

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    4714: PROBABILITY AND STATISTICS FOR ELECTRICAL ENGINEERS

    Introduction to the concepts of probability, random variables, estimation, hypothesis testing, regression, and analysis of variance with emphasis on application in electrical engineering. Only one of the courses 4604, 4705, and 4714 may be taken for credit. Pre: MATH 2224. (3H,3C). I,II,III.

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    4724: STATISTICAL THEORY FOR ECONOMISTS

    Probability, random variables, marginal and conditional distributions, mathematical expectations, sampling distributions, properties of estimators, maximum likelihood and least squares estimation, confidence intervals, hypothesis tests, linear regression. Emphasis on preparation for graduate study in econometrics. Pre: 3006 and MATH 2016. (3H,3C). I.

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    4804 (AAEC 4804): ELEMENTARY ECONOMETRICS

    Economic applications of mathematical and statistical techniques: regression, estimators, hypothesis testing, lagged variables, discrete variables, violations of assumptions, simultaneous equations. Pre: STAT 3005 or 3604 and AAEC 1006. (3H,3C). II.

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    4974: INDEPENDENT STUDY

    Variable credit course.

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    4984: SPECIAL STUDY

    Variable credit course.

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    4994: UNDERGRADUATE RESEARCH

    Variable credit course.

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    Advanced Undergraduate Courses (Stat)

    All 4000-level statistics courses may be taken for graduate credit by non-statistics majors. Statistics graduate students may not take 4000-level statistics courses for graduate credit.

     

    4004: METHODS OF STATISTICAL COMPUTING
    4105-4106: THEORETICAL STATISTICS
    4204: EXPERIMENTAL DESIGNS
    4214: METHODS OF REGRESSION ANALYSIS
    4504: APPLIED MULTIVARIATE ANALYSIS
    4514: CONTINGENCY TABLE ANALYSIS
    4524: SAMPLE SURVEY METHODS
    4604: STATISTICAL METHODS FOR ENGINEERS
    4705-4706: PROBABILITY AND STATISTICS FOR ENGINEERS
    4714: PROBABILITY AND STATISTICS FOR ELECTRICAL ENGINEERS
    4724: STATISTICAL THEORY FOR ECONOMISTS
    4804 (AGEC 4804): ELEMENTARY ECONOMETRICS

    Link to all undergraduate course syllabi

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    Graduate Statistics Courses (STAT)

    Link to all graduate course syllabi.

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    5014: INTRODUCTION TO STATISTICAL PROGRAM PACKAGES

    Introduction to computing facilities (mainframe and microcomputers), conversational monitoring system (CMS), and statistical program computer packages. Pass/Fail only. Pre: Graduate standing in Statistics.; Co: 5004. (1H,1C). I.

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    5024 (4964): EFFECTIVE COMMUNICATION IN STATISTICAL CONSULTING

    Oral communication of statistical concepts. Effective methods of statistical consulting. Presentation and discussion of statistical consulting projects. Pre: 5124 and 5204; (2H,2C). II.

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    5034: INFERENCE FUNDAMENTALS WITH APPLICATIONS TO CATEGORICAL DATA

    Fundamental ideas of statistical estimation and testing; principles and methods for standard one-sample settings; applications to categorical data problems. Topics include probability distributions, means, variances, and independence; point and interval estimation, including small and large sample procedures; hypothesis testing including exact and large-sample tests; goodness-of-fit; categorical data analysis; log-linear models; simple logistic regression. Pre: 5615, MATH/STAT 4584. Co: 5014. (3H, 3C).

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    5044: REGRESSION AND ANALYSIS OF VARIANCE

    Principles and methods of data analysis employing linear models for continuous response variables. Topics include both classical descriptive measures and modern computer-based techniques for data visualization; simple, multiple and weighted regression; analysis of variance for one-way and higher-way classifications; fixed, mixed, and random effects models; analysis of covariance; detection and correction of modeling flaws; statistical power. Pre: 5615, MATH/STAT 4584. Co: 5014. (3H,3C).

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    5104: PROBABILITY AND DISTRIBUTION THEORY

    Fundamental concepts of probability, random variables and their distributions, functions of random variables, mathematical expectations, and stochastic convergence. Pre: MATH 4526; (3H,3C). I.

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    5114: STATISTICAL INFERENCE

    Decision theoretic formulation of statistical inference, concept and methods of point and confidence set estimation, notion and theory of hypothesis testing, relation between confidence set estimation and hypothesis testing. Co: 5104. (3H,3C). II.

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    5124: LINEAR MODELS THEORY

    A study of the theory underlying the general linear model and general linear hypothesis. Applications in linear regression (full rank) and analysis of variance. Pre: 5114 and MATH 5524; (3H,3C). II.

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    5204: EXPERIMENTAL DESIGN AND ANALYSIS I

    Principles and concepts of experimental design; systematic overview and discussion of basic designs from the point of view of blocking, error reduction, and treatment structure; and development of analysis based on linear models. Pre: 5004 or 5616; (3H,3C). II.

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    5304: STATISTICAL COMPUTING

    Computational methods for statistical computing problems. Orthogonal transformations, sweep operators, and other numerical methods applied to general optimization techniques for maximum likelihood and least squares estimation problems. Pre: 5124, SAS programming language; (3H,3C). II. Alternate years.

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    5314: STATISTICAL SIMULATION

    Special computer techniques used in statistical simulation. Pseudo-random number generators, stochastic simulation, variance reduction techniques, and Monte Carlo applications. Pre: 5114 and Knowledge of Fortran; (3H,3C). II. Odd years.

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    5324: STATISTICAL METHODS FOR ANALYZING UNBALANCED DATA

    Discussion of statistical and computational aspects of methods for analyzing nonorthogonal data: estimable functions, estimation and testing of effects, and variance components for fixed, mixed, and random effects linear models; interpretation of output from existing computer packages. Pre: 5124 or 5204 or 5606 or 5616; (3H,3C). I. Alternate years.

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    5334: EXPLORATORY AND ROBUST DATA ANALYSIS

    Analysis of data by graphical and numerical techniques, statistical analysis of non-Gaussian data, topics in robust estimation for location, regression and correlation models, and the jackknife and bootstrap techniques. Pre: 5114, CMS; (3H,3C). I. Alternate years.

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    5344: LINEAR AND NONLINEAR PROGRAMMING

    Mathematical formulation and solution of linear and nonlinear programming problems; simplex algorithms (Kuhn-Tucker conditions, duality theory); and discussion of various applications in statistics. Pre: 4106 or 4706 and Matrix Algebra; (3H,3C). I. Even years.

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    5354: STRUCTURED PROCESS IMPROVEMENT

    An introduction to the selection, management, leadership and execution of structured process improvement projects. Topics include effective roadmaps for process improvement, team facilitation and leadership, project selection and management, sampling, process capability analysis, data transformations, variance component analysis, response surface methodology (including full and fractional factorial designs, Plackett-Burman designs, central composite designs, Box-Behnken designs, analysis of variance, regression, and multi-response optimization), and statistical process control. Pre: 5004 or 5624. (3H, 3C) I.

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    5404: NONPARAMETRIC STATISTICS

    Introduction to theory and methods of nonparametric statistical inference. General linear rank statistics, tests and estimation of location, dispersion, regression, and association. Selected topics. Pre: 5004, 5114; (3H,3C). I. Odd years

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    5414: TIME SERIES ANALYSIS I

    Analysis of data when observations are not mutually independent, stationary and nonstationary time series, linear filtering, trend elimination, prediction, and applications in economics and engineering. Pre: 5114; (3H,3C). I. Alternate years.

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    5424: STATISTICAL DECISION THEORY

    Decision theoretic approach to statistics including admissibility, minimax, and Bayes decisions. Theory and applications of Empirical Bayes. Pre: 5114; (3H,3C). II. Odd years.

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    5434: MARKOV CHAINS AND RENEWAL THEORY

    Basic definitions and characterization of states; limiting and hitting probabilities; Poisson process; pure jump Markov chains; renewal process and function; and renewal theorem. Pre: 5104; (3H,3C). II.

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    5444: BAYESIAN STATISTICS

    Introductory course of Bayesian statistics on basic concepts of probability, Bayesian inference of Normal, Binomial, Poisson, Uniform and other common distributions, selections of prior information, Bayesian decision theory, Bayesian analysis of regression and analysis of variance and Bayesian foundation. Pre: 5114; (3H,3C). II. Even years.

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    5454: RELIABILITY THEORY

    Basic concepts of lifetime distributions, types of censoring, inference procedures for exponential, Weibull and extreme value distributions, nonparametric estimation of survival function, kernel density estimation, accelerated life testing, and goodness of fit tests. Pre: 4106; (3H,3C). II. Alternate years.

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    5464 (ISE 5464): QUEUING THEORY

    Classic models of queues including M/M/1, M/GI/1, and GI/M/s. Topics in queue length processes, waiting time processes, busy period processes, and traffic processes. Pre: STAT 5434 or ISE 5414; (3H,3C). I. Even years.

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    5474 (ISE 5474): STATISTICAL THEORY OF QUALITY CONTROL

    Development of statistical concepts and theory underlying procedures used in quality control applications. Sampling inspection procedures, the sequential probability ratio test, continuous sampling procedures, process control procedures, and experimental design. Pre: STAT 5104 and 5114; (3H,3C). I. Alternate years.

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    5484: SEQUENTIAL ANALYSIS

    Introduction to sequential tests, sequential probability ratio and other tests, approximation to OC and ASN function, tests for continuous parameter processes, sequential tests between three hypotheses, invariant tests, and sequential estimation. Pre: 5114; (3H,3C). I. Alternate years.

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    5504: MULTIVARIATE STATISTICAL METHODS

    Methods of inference for multivariate distributions. Multivariate distributions, location and dispersion problems for one and two samples, multivariate analysis of variance, linear models, repeated measurements, inference for dispersion and association parameters, principal components, discriminant and cluster analysis, and simultaneous inference. Emphasis on robustness. Use of SAS. Pre: 4204 or 4706 or 5004 or 5616 and MATH 5524, CMS; (3H,3C). I. Even years.

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    5514: REGRESSION ANALYSIS

    Classical and modern techniques in regression analysis. Use of modern regression techniques to diagnose collinearity, leverage, and outliers. Model discrimination using cross validation techniques. The study of transformations, biased estimation, and nonlinear regression. Pre: 5124 or 5616; (3H,3C). I.

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    5524: SAMPLE SURVEY THEORY

    Theory of sample surveys including major sampling designs, sample size determination, estimation and interval estimation, and questionnaire design. Pre: 5004; (3H,3C). I. Alternate years.

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    5534: ANALYSIS OF MULTIVARIATE CATEGORICAL DATA

    Log-linear models for unconstrained and ordinal multidimensional contingency tables; testing and estimation; random and structural zeros; model building; logit models and logistic regression; and use of major statistical packages. Pre: 5124 and CMS; (3H,3C). I. Even years.

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    5544: SPATIAL STATISTICS

    Spatial data structures: geostatistical data, lattices, and point patterns. Stationary and isotropic random fields. Autocorrelated data structures. Semivariogram estimation and spatial prediction for geostatistical data. Mapped and sampled point patterns. Regular, completely random, and clustered point processes. Spatial regression and neighborhood analyses for data on lattices. Pre: 5124 (3H,3C). III. Even years.

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    5554: VARIANCE COMPONENTS

    Theoretical treatment of the general problem of estimating and testing hypotheses about variance components within the framework of random effects and mixed linear models; derivation of different estimation procedures and their statistical proper- ties; and discussion of balanced and unbalanced data and of designs for estimating variance components. Pre: 5124; (3H,3C). I. Alternate years.

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    5564: STATISTICAL GENETICS

    Probabilistic approach to behavior of random mating populations, effects of inbreeding and elementary selection, population fitness, and natural selection. Statistical concepts in quantitative inheritance for random and non-random mating populations, correlation between relatives, and artificial selection. Pre: 5004 or 5606 or 5616 and BIOL 3004; (3H,3C). II. Alternate years.

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    5574: RESPONSE SURFACE DESIGN AND ANALYSIS I

    Use of response surface analysis to design and analyze industrial experiments. First and second order models. First and second order experimental designs. Use of model diagnostics for finding optimum operating conditions. Pre: 5204; (3H,3C). I. Odd years.

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    5584 (AAEC 5584): BASIC TOPICS IN ECONOMETRICS

    Introduction to the concepts and methods in application of econometric analysis to problems of economic research. Pre: 4724; (3H,3C). II.

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    5594: TOPICS IN BIOSTATISTICS

    Course with variable content; specialized application of statistical theory and methodology to biological and medical sciences; topics include bioassay, epidemiology, survival analysis, and statistical ecology. May be repeated for credit with different topics. Pre: 5114; (3H,3C). III. Odd years.

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    5605-5606: BIOMETRY

    5605: The normal distribution, estimation, hypothesis testing, simple linear regression, and one-way analysis of variance with applications to the biological sciences.

    5606: Experimental design, nested and factorial analysis of variance, linear regression and correlation, and the use of SAS, with applications to the biological sciences.

    Pre: CMS for 5606. (3H,3C). 5605: I; 5606: II.

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    5615-5616: STATISTICS IN RESEARCH

    5615: Concepts in statistical inference, including basic probability, estimation, and test of hypothesis, point and interval estimation and inferences; categorical data analysis; simple linear regression; and one-way analysis of variance.
    5616: Multiple linear regression; multi-way classification analysis of variance; randomized block designs; nested designs; and analysis of covariance.
    Pre: 1 year calculus and CMS; (3H,3C). 5615: I,III; 5616: II,IV.

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    5624: MANAGERIAL STATISTICS

    Introduction to statistical concepts and methods: descriptive statistics, probability, and distributions; inferences for means, variances, and proportions; and regression and correlation. (3H,3C). I,II.

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    5634: STATISTICS FOR BEHAVIORAL SCIENCES

    Basic statistical methods used in research in the behavioral sciences with emphasis on the applications of these methods. Descriptive statistics, correlational analyses, and intermediate inferential methods will be discussed. X-grade allowed. (3H,3C). I,II,III.

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    5644: NONPARAMETRIC STATISTICAL METHODS

    Applications of rank-order statistics, sign statistics, the empirical distribution function, and runs to commonly occurring data structures. Emphasis on concepts, assumptions, comparisons to normal theory methods, and hands-on data analysis with the computer. Pre: 3006 or 4706 or 5004 or 5606 or 5616 and CMS; (3H,3C). I.

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    5654: MEASURES OF ASSOCIATION

    Statistical methods of measuring association between nominal, ordinal, or interval level variables. Tests for significance of association. Use of two-group tests and analysis of variance to explore mixed mode relationships, such as between nominal and interval level variables. Prediction models for interval level measurements. (3H,3C). I.

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    5665-5666: STATISTICS FOR SOCIAL SCIENCE RESEARCH

    5665: Basic concepts of statistical inference, including probability, point and interval estimation, hypothesis testing logic; one-sample and two-sample tests on means, variances and proportions; one-way and two-way analysis of variance; multiple comparison procedures.

    5666: Multi-way analysis of variance; nested designs; repeated measures experiments; correlation for discrete and continuous variables; simple and multiple linear regression.
    Pre: College Algebra and CMS.; (3H,3C). 5665: I; 5666: I,II.

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    5894: FINAL EXAMINATION

    Pass/fail only. (3H,3C).

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    5904: PROJECT AND REPORT

    Variable credit course. I,II,III,IV,V.

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    5924: GRADUATE SEMINAR

    Special topics in statistical theory and applications. May be taken for credit two times (max. 2C). Pass/Fail only. Pre: Graduate standing; (1H,1C). I,II.

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    5974: INDEPENDENT STUDY

    Pass/fail only. Variable credit course.

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    5984: SPECIAL STUDY

    Variable credit course.

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    5994: RESEARCH AND THESIS

    Variable credit course.

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    6105-6106 (MATH 6105-6106): MEASURE AND PROBABILITY

    Development of measure theoretic foundations of probability theory.
    6105: sigma fields, probability, and general measures; random variables, measurability and distributions, integration, and expectation; product measures; Radon-Nikodym theorem and conditioning.
    6106: Random variables and strong and weak laws of large numbers; characteristic functions, central limit theorem and martingales; stochastic processes and Brownian motion. 6105 partially duplicates Math 5225.
    Pre: STAT 5104 or MATH 4525; (3H,3C). 6105: I; 6106: II.

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    6114: ADVANCED TOPICS IN STATISTICAL INFERENCE

    Advanced course in the theory of inference for graduate students in statistics and other qualified graduate students. Develops foundations, sufficiency, information, estimation, hypothesis testing, invariance, and unbiasedness. Pre: 5114, 6105; (3H,3C). II.

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    6404: ADVANCED TOPICS IN NONPARAMETRIC STATISTICS

    Topics of current interest in research for nonparametric theory and methods, using recent advanced texts and journal articles. Pre: 5404, 6114; (3H,3C). II. Odd years. Alternate years.

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    6414: TIME SERIES ANALYSIS II

    Weakly and strictly stationary stochastic processes; ergodic and ensemble theory; time and frequency domain; spectral decomposition theory; Hilbert space geometry; and multivariate spectra. Pre: 5414; (3H,3C). II. Alternate years.

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    6424: MULTIVARIATE STATISTICAL ANALYSIS

    Foundations of multivariate analysis. Distribution theory of vectors and matrices, inequalities, limit theory, the structure of some multivariate location-scale parameter families, derived distributions, invariant distributions, the principle of invariance in estimation and testing for multivariate location and scale parameters, and robust aspects of normal-theory multivariate procedures. Pre: 5504; (3H,3C). II. Odd years.

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    6434: STATIONARY AND RELATED PROCESSES

    Stationary processes, harmonic analysis, prediction, ARMA and moving average processes, martingales, and elementary stochastic integrals and differential equations. Pre: 5104; (3H,3C). I. Alternate years.

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    6464 (ISE 6464): QUEUING NETWORKS

    Applications of queuing theory results to queuing networks. Topics include reversibility, insensitivity, product forms for queue length processes, and traffic processes including traffic flow within the network. Pre: ISE 5644, 6504; (3H,3C).

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    6484 (ISE 6484): SEMINAR IN APPLIED PROBABILITY

    Working seminar open to anyone doing research in applied probability. The purpose is to review student research progress through a series of seminars offered by them and to present new research results offered by faculty attending. May be taken more than once. Pre: Enrollment in Ph.D. program; (1H,1C). I,II.

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    6494: ADVANCED TOPICS IN MATHEMATICAL STATISTICS

    Advanced treatment beyond standard course offerings in topics such as theory of inference, nonparametrics, sequential analysis, and limit theory. May be repeated for credit with different topics. Pre: 5114 and consent; (3H,3C). II.

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    6504: EXPERIMENTAL DESIGN AND ANALYSIS II

    Theoretical treatment of construction and analysis of various types of incomplete block and factorial designs. Pre: 5124, 5204; (3H,3C). I. Alternate years.

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    6514: ADVANCED TOPICS IN REGRESSION

    Advanced notions in modern regression techniques and diagnostics. Advanced study of nonlinear models, generalized linear models, generalized estimating equations, and mixed linear and nonlinear models. Pre: 5124 and 5514; (3H,3C). II. Even years.

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    6574: RESPONSE SURFACE DESIGN AND ANALYSIS II

    Advanced techniques and theory in response surface analysis and design. Robustness of designs. Thorough study of the notion of rotatability. Optimal design criteria and designs for estimating slopes of response surfaces. Mixture designs. Study of model misspecification. Pre: 5574; (3H,3C). II. Odd years.

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    6584 (AAEC 6584): ADVANCED TOPICS IN ECONOMETRICS

    Advanced topics in the theory of econometrics, and the uses of advanced techniques in application to empirical problems. Pre: 5584; (3H,3C). I.

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    6634 (EDRE 6634): ADVANCED STATISTICS FOR EDUCATION

    Multiple regression procedures for analyzing data as applied in educational settings, including curvilinear regressions, dummy variables, multicollinearity, and introduction to path analysis. Pre: STAT 5634; (3H,3C). II.

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    6644 (EDRE 6644): ADVANCED RESEARCH DESIGN AND METHODOLOGY

    Principles of experimental design with applications to the behavioral sciences emphasizing appropriate statistical analysis. Pre: STAT 5634; (3H,3C).

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    7994: RESEARCH AND DISSERTATION

    Variable credit course.

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    Link to all graduate course syllabi.