Course Matrix

Statistical Methodology: Campuswide

We would like to bring these methodology courses to your attention.

This is a growing list. If you know of a course that we have missed, please let us know. We are aware of the fact that many of the courses listed here are not offered in any particular semester and have requested a revision of the software from the KU IT team to display only the courses that will actually be offered.

We are willing/able to insert additional comments and explanations for courses if professors submit them at crmda@ku.edu

Upper-level Undergraduate 

SOC 510 Elementary Statistics and Data Analysis
An introduction to social scientific data analysis, with an emphasis on descriptive and inferential statistics. Specific topics include sampling, measures of association and correlation, significance testing, the logic of causal inference, the use of computer programs for data analysis, multivariate analysis, and the critical evaluation of social science research findings. Prerequisite: SOC 310 and MATH 101, or instructor permission. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Rauscher, Emily
TR 11:00-12:15 PM FR 106 - LAWRENCE
3 18059

PSYC 500 Intermediate Statistics in Psychological Research
A second course in statistics with emphasis on applications. Analysis of variance, regression, analysis, analysis of contingency tables; possibly selected further topics. Prerequisite: Grade of B- or better in PSYC 210 or PSYC 211. LEC.

The class is not offered for the Fall 2017 semester.

Design & Research Methods

POLS 705 Research Design for Political Science
Introduction to the discipline of political science, the philosophy of science, research design, and data acquisition. Prerequisite: Graduate standing or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Miller, Patrick
APPT- ONLNE KULC - LAWRENCE
3 23635

EPSY 715 Understanding Research in Education
This course introduces the concepts and skills involved in understanding and analyzing research in education and related areas. The course provides an overview of basic, general knowledge of various research methodologies. Students should expect to study much of this material in greater depth through additional course work before being fully prepared to conduct independent research. However this course should enhance their ability to locate, read, comprehend, and critically analyze research articles and reports. Topics in the course include quantitative and qualitative methods and designs, historical and descriptive research, and program evaluation. (This course fulfills the requirement of a research methods course in the first 12 hours of graduate study.) LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Peyton, Vicki
APPT- ONLNE KULC - LAWRENCE
3 14357
LEC Peyton, Vicki
APPT- ONLNE KUEC - EDWARDS
3 18007
LEC Peyton, Vicki
APPT- ONLNE PROG - ONLINL
3 24676
LEC Peyton, Vicki
APPT- ONLNE PROG - ONLINL
3 22601

EPSY 725 Educational Measurement
The course is an introduction to the application of the concepts of reliability, validity, and practicality to the development, selection, use, and interpretation of tests and other measuring instruments in the field of education. The concepts of norm referenced and criterion referenced tests; the interpretation and use of norms; standard scores, percentiles, quotients, and grade equivalents are among the topics covered. An understanding of the role of measurement in evaluation, diagnosis, selection and placement is included. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Frey, Bruce
M 04:30-07:00 PM JRP 246 - LAWRENCE
3 16160

EPSY 923 Advanced Theory and Applications of Item Response Theory
This course is designed to acquaint students with knowledge of advanced theory and applications in the field of item response theory (IRT). Topics to be covered include: advanced IRT models for dichotomous and polytomous, multidimensional, rater effects, and testlet-based item response data, estimation of parameters for these models and related software, and goodness of fit tests. The course will also focus on some advanced applications using these models, including test development, test score equating, differential item functioning, scoring and score reporting, Monte Carlo simulation studies, and innovative test designs. Prerequisite: EPSY 922 or equivalent course. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 980 Advanced Topics: _____
A special course of study to meet current need of education professionals--primarily for post-master's level students. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Kingston, Neal
M 01:30-04:00 PM JRP 622 - LAWRENCE
1-3 25839

ECON 870 Applied Microeconomics
This course introduces students to the data and empirical methods used in the fields of applied economics such as labor economics, public finance, and industrial organization. The course will focus on how to adjust for self-selection and identify causal relationships in applied microeconomic fields. Topics covered include economic data and statistical programming, instrumental variables, difference-in-differences, regression discontinuity, count data, sample selection, treatment effects, and duration models. Attention will be given to the suitability of the methods to the research question under consideration. Each topic will emphasize the proper application of the methods using the standard textbook treatment as well as assigned papers that examine the basic economic issues, the econometric techniques, and the applications to data. Prerequisite: ECON 817 and ECON 818, or consent of instructor. ECON 915 is recommended. LEC.

The class is not offered for the Fall 2017 semester.

SPLH 861 Seminar in Research Methodology in Speech Pathology and Audiology: _____
This seminar is concerned with the design, instrumentation, execution, and reporting of research in audiology and speech pathology. SPLH 760 or its equivalent and some statistics are recommended before entering this seminar. LEC.

The class is not offered for the Fall 2017 semester.

Statistics (Regression, Analysis of Variance, Econometrics).

ECON 715 Elementary Econometrics
An elementary analysis of the problems of estimation, prediction, and hypothesis testing in the context of general linear, stochastic difference equation and simultaneous equations models. Applications of econometric theory to practical economic problems will be emphasized. Prerequisite: DSCI 301 or its equivalent; MATH 116 or MATH 121; and completion of ECON 142 and ECON 144, ECON 520, and ECON 522 with a grade-point average of at least 3.00 (B) or graduate standing. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Iwata, Shigeru
TR 08:00-09:15 AM SNOW 358 - LAWRENCE
3 11240
ECON 716 Econometric Forecasting
An analysis of econometric forecasting techniques, including time-series models, single-equation regression models, and multiple-equation regression models. The course will examine forecasts of (a) macroeconomic variables, such as interest rates, investment, GNP, and the rate of inflation; and (b) market variables, such as price and quantity. Prerequisite: ECON 715 or ECON 817. LEC.

The class is not offered for the Fall 2017 semester.

POLS 706 Research Methods I
An introduction to quantitative research methods, including probability theory, hypothesis-tests, and multiple regression. Includes regression diagnostics, the treatment of numeric and categorical predictors, interaction effects and elementary nonlinear models. Applications across the behavioral and social sciences are emphasized. Course consists of three hours of lecture and lab sessions where computing applications are taught. LEC.

The class is not offered for the Fall 2017 semester.

POLS 707 Research Methods II
This course covers basic techniques for multivariate analysis, focusing on multiple regression. Topics include interpretation of regression statistics, diagnostics for common problems, dummy variables, instrumental variables, basic time series methods including adjustment for autocorrelated error, logistic models, and nonlinear modeling; additional techniques may be covered at the discretion of the instructor. Prerequisite: POLS 706. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Webb, Clayton
R 04:00-07:00 PM BL 109 - LAWRENCE
3 22065

POLS 906 Advanced Regression
Covers topics appropriate for a second course in regression analysis. The content will vary according to the interest of the instructor and students, but will generally include such topics as multiple imputation of missing data, the generalized linear model (GLM), and specialized models for longitudinal data. The course will include a review of the principles of maximum likelihood estimation and applications of matrix algebra and differential calculus in statistical applications. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 710 Introduction to Statistical Analysis
Emphasis on the conceptual underpinnings of statistical analysis of educational data. Includes univariate and bivariate descriptive statistics, sampling distributions, statistical estimation, hypothesis testing and procedures in testing statistical hypothesis for one and two sample designs. Prerequisite: Concurrent enrollment in EPSY 711 required, or with the permission of instructor on the basis of knowledge of statistical packages presented in EPSY 711. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Peyton, Vicki
W 04:30-07:00 PM JRP 201 - LAWRENCE
3 13376

PSYC 790 Statistical Methods in Psychology I
Elementary distribution theory; t-test; simple regression and correlation; multiple regression and multiple correlation; curvilinear regression; logistic regression; general linear model. Applications across the behavioral and social sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: A beginning course in statistics and graduate standing, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Wu, Wei
MW 11:00-12:45 PM FR 547 - LAWRENCE
4 24402

PSYC 791 Statistical Methods in Psychology II
Continuation of PSYC 790. One-way analysis of variance, linear trends, contrasts, post hoc tests; multi-way analysis of variance for crossed, blocked, nested, and incomplete designs; analysis of covariance; repeated measures analysis of variance; general linear model. Applications across the social, educational, and behavior sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 810 Regression Analysis
Multiple correlation/regression techniques, including polynomials, analysis of interactions, dummy coding, non-orthogonal analysis of variance, and analysis of covariance. Prerequisite: EPSY 710 or equivalent course. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Peyton, Vicki
T 04:30-07:00 PM JRP 247 - LAWRENCE
3 16404

EPSY 811 Analysis of Variance
Analysis of variance techniques including one-way ANOVA, planned and post hoc comparisons, multiway ANOVA, repeated measures ANOVA, and mixed designs. Prerequisite: EPSY 710 and EPSY 711. LEC.

The class is not offered for the Fall 2017 semester.

ECON 817 Econometrics I
An intensive study of the general linear model and distribution theory associated with the multivariate normal; stochastic difference equation; autocorrelation, errors in variables. Prerequisite: MATH 628. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Cai, Zongwu
TR 02:30-03:45 PM SNOW 358 - LAWRENCE
3 14857
 
ECON 818 Econometrics II
The study of estimation and hypothesis testing within the context of the stochastic simultaneous equations model. Prerequisite: ECON 817. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 815 Design and Analysis for Developmental Research
Coverage of the philosophy and basic principles of group-design research, with a special emphasis on designs that are appropriate for developmental studies. Designs for both experimental and quasi-experimental research are covered, and appropriate statistical procedures are presented concomitantly with the designs. Individual-difference analyses and statistical control issues are also addressed. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Hall, Amber
W 09:30-12:20 PM DHDC 2009 - LAWRENCE
3 22470

PSYC 816 Design and Analysis for Neuroimaging Research
Course covers research design and analysis issues for event-related potential (ERP) and functional magnetic resonance imaging (fMRI) studies. Repeated measures, statistical parametric mapping, principal components analysis, and independent components analysis techniques are covered. Both practical and theoretical aspects of these statistical techniques will be explored in Matlab environment. Matrix algebra recommended but not required. Prerequisite: PSYC 790 and 791 or equivalent are required. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 818 Experimental Research Methods in Social Psychology
Systematic discussion of the techniques of research in social psychology, with practice in the utilization of selected methods. Prerequisite: One course in social psychology in addition to introductory social psychology. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Branscombe, Nyla
M 01:00-03:50 PM KSUN ALCG - LAWRENCE
M 01:00-03:50 PM KSUN INTL - LAWRENCE
M 01:00-03:50 PM KSUN ALCG - LAWRENCE
3 18481

PSYC 819 Field and Evaluation Research Methods in Social Psychology
Basic principles and practices of field methods in basic and applied research in social psychology and related fields; relationships between field and laboratory studies; special emphasis on survey and evaluation research methods and study designs; client and respondent relationships; research and public policy. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 887 Factor Analysis
This course covers the theory behind, and application of, exploratory factor analysis. Topics include a review of multiple linear regression and matrix algebra. In-depth coverage is devoted to diagrams, model specification, goodness of fit, model selection, parameter estimation, rotation methods, scale development, and sample size and power issues. Extensions to confirmatory settings are elaborated. Both the theory underlying factor analytic techniques and hands-on application using software are emphasized. Applications across the social and behavioral sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Brandt, Holger
R 09:00-11:50 AM FR 327 - LAWRENCE
4 24629

PSYC 893 Multivariate Analysis
Introduction to the central methods used in the analysis of multivariate data. Includes linear transformations, multivariate analysis of variance, multivariate multiple regression, discriminant analysis, canonical correlation, factor analysis, and an introduction to methods for clustering and classification. Applications across the behavior and social sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 894 Multilevel Modeling
Statistical methods for modeling multilevel (hierarchically structured) data. Topics include a review of ordinary least squares regression analysis, random effects ANOVA, intraclass correlation, multilevel regression, testing and probing interactions, maximum likelihood estimation, model assumptions, model evaluation, and the analysis of longitudinal data. There will be a heavy emphasis on the theory underlying multilevel modeling techniques and hands-on application using software. Applications across the social, educational, and behavior sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Brandt, Holger
R 01:00-03:50 PM FR 327 - LAWRENCE
4 24422

PSYC 895 Categorical Data Analysis
Multivariate analyses of count data. Error models, statistical inference, loglinear models, logit models, logistic regression. Homogeneity, symmetry, and selected other topics. Applications across the behavioral and social sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 896 Structural Equation Modeling I
Introduction to statistical methods for modeling latent variables. Topics include a review latent variables, covariance structures analysis, mean structures analysis, confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple group CFA, longitudinal CFA, longitudinal SEM, Hierarchical CFA, and Multi-trait Multi-Method SEM. Applications across the behavioral and social sciences are emphasized. Course consists of three hours of lecture and a required one-hour lab session where computing applications are taught. Prerequisite: PSYC 790 or equivalent, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Wu, Wei
T 01:00-04:50 PM FR 327 - LAWRENCE
4 24112

EPSY 905 Multivariate Analysis
Multivariate analysis of variance, discriminant analysis, logistic regression, and exploratory factor analysis. Prerequisite: EPSY 810, EPSY 811 and experience with a statistical software package. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 998 Seminar in: _____
Course is graded on a satisfactory/fail basis. LEC.

The class is not offered for the Fall 2017 semester.

DSCI 920 Probability for Business Research
(F) This course covers the basic theory of probability and its use for research in the business disciplines. The course is designed primarily for Ph.D. students in the business school. Prerequisite: Doctoral standing and two semesters of calculus, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Shenoy, Prakash
APPT- KULC APPT - LAWRENCE
4 17769

DSCI 921 Statistics for Business Research
(S) This course covers the basic theory of statistics and its use for research in the business disciplines. The course is designed primarily for Ph.D. students in the School of Business. Prerequisite: DSCI 920. LEC.

The class is not offered for the Fall 2017 semester.

ECON 915 Advanced Econometrics I
The study of selected topics in applied cross-section econometrics for uses mainly in applied microeconomics, public finance, and labor economics. Topics include traditional econometrics of production and demand, latent variable models, panel data studies, probabilistic choice models, censored and truncated models, sample selection, disequilibrium models, duration studies, and semi- and non-parametric models. Prerequisite: ECON 818, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

ECON 916 Advanced Econometrics II
A study of selected topics in applied time-series econometrics for use mainly in applied macroeconomics, international finance, and development economics. Topics include empirical applications of ARCH models, VAR models (study of impulse response function and variance decomposition), unit-root cointegration and long memory models. Bayesian unit root analysis, estimation and inference of dynamic general equilibrium models, model calibration and simulation are also possible topics of this course. Prerequisite: ECON 818, or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Iwata, Shigeru
TR 09:30-10:45 AM SNOW 358 - LAWRENCE
3 25860
ECON 917 Advanced Econometrics III
A study of structural and nonlinear time series approaches to econometric modeling and inference. The course emphasizes techniques needed to use economic theory in system-wide econometrics. Emphasis is placed on selection of functional form for approximation to theoretical functions and the use of duality theorems for derivation of the resulting econometric systems of equation. Inference with those models will be by nonlinear parametric, semi-parametric, and nonparametric methods. Prerequisite: ECON 818. LEC.

The class is not offered for the Fall 2017 semester.

 
POLS 904 Statistical Computing Foundations
This is an interdisciplinary course for social science researchers who need to develop routines to estimate and evaluate statistical models. It introduces tools for software development, primarily with the statistical programming language R (and related languages like C). Topics include code organization and optimization, concurrent version management, LaTeX document preparation, and high-performance computing on the KU Linux cluster. Examples from various fields are considered. Prerequisite: Two courses in graduate level statistics and familiarity with R. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Johnson, Paul
W 05:00-07:50 PM BL 114 - LAWRENCE
3 25950
 
POLS 909 Topics in Methodology: ______
An intensive seminar in a method (or a variety of relevant methods) of theoretical or empirical research designed for Ph.D. students only. Emphasis is on deepening the understanding and ability to use advanced methods of analysis. Prerequisite: Admission to the Ph.D. program or consent of instructor. RSH.

The class is not offered for the Fall 2017 semester.

PSYC 990 Methods for Clustering and Classification
Statistical methods for identifying classes, clusters, and taxa. Topics include k-means, discriminant analysis, hierarchical clustering algorithms, additive trees, neural network models for clustering, latent class models, finite mixture models, and models for skills/cognitive diagnosis. Applications across the social and behavior sciences are emphasized. Prerequisite: PSYC 790 and PSYC 791 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 991 Longitudinal Data Analysis
Reviews and contrasts various statistical methods for the analysis of change. Course focuses on various techniques to analyze longitudinal (repeated-measures) data beyond the repeated-measures ANOVA framework. Techniques covered included latent change scores, latent difference scores, individual-differences modeling of latent residual and change scores, intra-individual differences modeling (e.g., growth curve, mixed modeling) and growth mixture modeling. Applications across the behavioral and social sciences are emphasized. Prerequisite: PSYC 896 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

PSYC 996 Structural Equation Modeling II
Continuation of PSYC 896. Advanced applications of modern methods for testing hypotheses on multivariate correlational data in the behavioral and social sciences. Topics include advanced confirmatory factor analysis, mediation and moderation among latent variables, latent growth curve modeling, and other latent variable mean and covariance structures analysis techniques. Applications across the behavioral and social sciences are emphasized. Prerequisite: PSYC 896 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

DSCI 935 Seminar in Optimization: _____
(V) This course will cover basic and advanced topics in optimization theory and applications. Examples of topics that may be covered are linear programming, nonlinear programming, dynamic programming, multiple-criteria decision making, habitual domain theory for forming winning strategies and effective decision making and game theory. Prerequisite: Linear algebra and real analysis or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

Biostatistics

BIOS 740 Applied Multivariate Methods
This course is an advanced statistical course for students who have had fundamental biostatistics and linear regression. Topics to be covered include Hotelling's T-squared test, MANOVA, principal components, factor analysis, discriminant analysis, canonical analysis, and cluster analysis. More advanced topics such as Multidimensional Scaling or Structural Equation Modeling might be introduced if time allows. Computers will be extensively used through the whole course, and students are suggested to be familiar with some statistical software before taking this course. Although students are allowed to use the software they are comfortable with, SAS will be the primary statistical package used to demonstrate examples in this course. Prerequisite: Corequisite: BIOS 730 or equivalent with permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

BIOS 871 Mathematical Statistics
This course introduces the fundamentals of probability theory, random variables, distribution and density functions, expectations, transformations of random variables, moment generating functions, convergence concepts, sampling distributions, and order statistics. Prerequisite: By permission of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Habiger, Joshua
TR 09:30-10:50 AM - KUMC-K
3 17989

BIOS 872 Mathematical Statistics II
This course introduces the fundamentals of statistical estimation and hypothesis testing, including point and interval estimation, likelihood and sufficiency principles, properties of estimators, loss functions, Bayesian analysis, and asymptotic convergence. Prerequisite: BIOS 871 or by permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

Item Response Theory & Test Assessment

PSYC 892 Test Theory
This course begins with recommendations for how to write a test (with or without correct answers, for assessing a wide variety of constructs of interest in social and behavioral sciences), covers basics of classical test theory, and then emphasizes modern statistical methods for analyzing item data. Methods include factor analysis of categorical responses, methods for identifying measurement invariance (differential item functioning), and item response theory. Lectures and Laboratory. This course is offered at the 600 and 800 levels, with additional assignments at the 800 level. Prerequisite: PSYC 790/650 or equivalent, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 921 Theory and Applications of Educational Measurement
Application of theory including classical theories of reliability and validity, latent-trait theories, item sampling, and factor analysis to problems in educational test development and use in areas such as evaluation, research, placement, and selection. Prerequisite: EPSY 725 and EPSY 811. LEC.

The class is not offered for the Fall 2017 semester.

EPSY 922 Item Response Theory
Theoretical foundations and practical applications of item response theory in educational measurement. Prerequisite: EPSY 921. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Skorupski, William
R 01:30-04:20 PM JRP 622 - LAWRENCE
3 25837

EPSY 980 Advanced Topics: _____
A special course of study to meet current need of education professionals--primarily for post-master's level students. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Kingston, Neal
M 01:30-04:00 PM JRP 622 - LAWRENCE
1-3 25839

Note: EPSY 980 Advanced Topics in Research, Evaluation, Measurement and Statistics will be offered in the Fall each year. Topics addressed may include assessment for international comparisons, special populations, item bias, and sensitivity review.

Technical Foundations

ECON 800 Optimization Techniques I
Economic models involving the maximation of a scalar (vector) function subject to equality and inequality constraint where the variables are in a finite dimensional Euclidean space. Characterization of optimal points by way of first and second order derivatives and by way of saddle points. Duality theorems of mathematical programming. Prerequisite: Consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Zhang, Jianbo
Cornet, Bernard
MW 03:00-04:15 PM SNOW 452 - LAWRENCE
3 15267

ECON 809 Optimization Techniques II
Economic models involving the maximization of an integral (a vector of integrals) subject to differential equality (inequality), integral equality (inequality), and finite equality (inequality) constraints. Characterization of optimal paths by way of first and second derivatives. Existence of optimal paths. Prerequisite: Consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

MATH 581 Numerical Methods
An introduction to numerical methods and their application to engineering and science problems. Applied treatment of elementary algorithms selected from the subject areas: finding roots of a single nonlinear equation, numerical differentiation and integration, numerical solution of ordinary differential equations. Emphasis on implementing numerical algorithms using the computer. Not open to students with credit in MATH 781 or MATH 782. Prerequisite: MATH 220 and MATH 290, or MATH 320. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Van Vleck, Erik
TR 11:00-12:15 PM SNOW 152 - LAWRENCE
3 14528

MATH 590 Linear Algebra
Vector spaces, linear transformations, and matrices. Canonical forms, Determinants. Hermitian, unitary and normal transformations. Not open to students with credit in MATH 792. Prerequisite: MATH 127 or MATH 147 or MATH 223 or MATH 243, and MATH 290 or MATH 291. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Tu, Xuemin
MWF 10:00-10:50 AM SNOW 152 - LAWRENCE
3 12414
LEC Hernandez, Daniel
TR 11:00-12:15 PM SNOW 156 - LAWRENCE
3 22948
MATH 591 Applied Numerical Linear Algebra
An introduction to numerical linear algebra. Possible topics include: applied canonical forms, matrix factorizations, perturbation theory, systems of linear equations, linear least squares, singular value decomposition, algebraic eigenvalue problems, matrix functions, and the use of computational software. Not open to students with credit in MATH 780 or MATH 782. Prerequisite: MATH 290 or MATH 291. EECS 138 or equivalent recommended. LEC.

The class is not offered for the Fall 2017 semester.

MATH 611 Time Series Analysis
An introduction to the theory and computational techniques in time series analysis. Descriptive techniques: trends, seasonality, autocorrelations. Time series models: autoregressive, moving average, ARIMA models; model specification and fitting, estimation, testing, residual analysis, forecasting. Stationary processes in the frequency domain: Fourier methods and the spectral density, periodograms, smoothing, spectral window. Prerequisite: MATH 122 and a calculus based statistics course. LEC.

The class is not offered for the Fall 2017 semester.

MATH 781 Numerical Analysis I
Finite and divided differences. Interpolation, numerical differentiation, and integration. Gaussian quadrature. Numerical integration of ordinary differential equations. Curve fitting. (Same as EECS 781.) Prerequisite: MATH 320 and knowledge of a programming language. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Tu, Xuemin
TR 09:30-10:45 AM SNOW 152 - LAWRENCE
3 12436
MATH 782 Numerical Analysis II
Direct and iterative methods for solving systems of linear equations. Numerical solution of partial differential equations. Numerical determination of eigenvectors and eigenvalues. Solution of nonlinear equations. (Same as EECS 782.) Prerequisite: MATH 781. LEC.

The class is not offered for the Fall 2017 semester.

MATH 647 Applied Partial Differential Equations
Boundary value problems; topics on partial differentiation; theory of characteristic curves; partial differential equations of mathematical physics. Prerequisite: MATH 127 or MATH 147 or MATH 223 or MATH 243, and MATH 220 or MATH 221 or MATH 320. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Stanislavova, Milena
MWF 10:00-10:50 AM SNOW 302 - LAWRENCE
3 12416
MATH 648 Calculus of Variations and Integral Equations
Topics in the calculus of variations, integral equations, and applications. Prerequisite: MATH 127 or MATH 147 or MATH 223 or MATH 243, and MATH 220 or MATH 221 or MATH 320. LEC.

The class is not offered for the Fall 2017 semester.

MATH 850 Differential Equations and Dynamical Systems
Discrete and differentiable dynamical systems with an emphasis on the qualitative theory. Topics to be covered include review of linear systems, existence and uniqueness theorems, flows and discrete dynamical systems, linearization (Hartman-Grobman theorem), stable and unstable manifolds, Poincare sections, normal forms, Hamiltonian systems, and an introduction to bifurcation theory and chaos. Prerequisite: MATH 320 and MATH 766, or permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

Bayesian Statistics

DSCI 934's full name is Seminar in Probability & Statistics: Probabilistic Graphical Models:

DSCI 934 Seminar in Probability and Statistics:_____
(V) This course will cover advanced topics in probability and statistics with application to various business disciplines. Topics covered may vary and will depend on the instructor. Examples of topics that may be covered are time series models, stochastic processes, uncertainty in artificial intelligence, multivariate statistics, etc. Prerequisite: DSCI 920 and DSCI 921, or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

"Big Data" and Machine Learning

EECS 738 Machine Learning
"Machine learning is the study of computer algorithms that improve automatically through experience" (Tom Mitchell). This course introduces basic concepts and algorithms in machine learning. A variety of topics such as Bayesian decision theory, dimensionality reduction, clustering, neural networks, hidden Markov models, combining multiple learners, reinforcement learning, Bayesian learning etc. will be covered. Prerequisite: Graduate standing in CS or CoE or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

EECS 837 Data Mining
Extracting data from data bases to data warehouses. Preprocessing of data: handling incomplete, uncertain, and vague data sets. Discretization methods. Methodology of learning from examples: rules of generalization, control strategies. Typical learning systems: ID3, AQ, C4.5, and LERS. Validation of knowledge. Visualization of knowledge bases. Data mining under uncertainty, using approaches based on probability theory, fuzzy set theory, and rough set theory. Prerequisite: Graduate standing in CS or CoE or consent of instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Grzymala-Busse, Jerzy
TR 08:00-09:15 AM LEA 1136 - LAWRENCE
3 25593

EECS 839 Mining Special Data
Problems associated with mining incomplete and numerical data. The MLEM2 algorithm for rule induction directly from incomplete and numerical data. Association analysis and the Apriori algorithm. KNN and other statistical methods. Mining financial data sets. Problems associated with imbalanced data sets and temporal data. Mining medical and biological data sets. Induction of rule generations. Validation of data mining: sensitivity, specificity, and ROC analysis. Prerequisite: Graduate standing in CS or CoE or consent of instructor. LEC.

The class is not offered for the Fall 2017 semester.

Applied Statistics & Analytics

STAT 810 Clinical Trials
The design, implementations, analysis, and assessment of controlled clinical trials. Basic biostatistical concepts and models will be emphasized. Issues of current concern to trialists will be explored. Prerequisite: Permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 820 Statistical Computing/SAS Base L1
This is a graduate level course preparing a student for the SAS base programming certification exam. We will cover the topics required for a student to pass the SAS base programming certification exam given by SAS. To this end, topics we will study will include, referencing files and setting options, creating list reports, understanding data step processing, creating and managing variables, reading and combining SAS data sets, do loops, arrays, and reading raw data from files. After the completion of the course the student should be able to create SAS programs to read data from external files, manipulate the data into variables to be used in an analysis, generate basic reports showing the results, be able to understand and explain results from univariate analyses using proc univariate. Prerequisite: Permission of Instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Keighley, John
APPT- ONLNE KUEC - EDWARDS-K
3 22835

STAT 821 Statistical Computing II
This is a graduate level course preparing a student for the SAS advanced programming certification exam. We will cover the topics required for a student to pass the SAS advanced programming certification exam given by SAS. To this end, topics we will study include array processing, use of data step views, using the data step to write SAS programs, efficient use of the sort procedure, introduction to the macro language in SAS, and accessing data using SAS PROC SQL. After the completion of the course, the student should be able to create SAS programs to read data from external files, manipulate the data into variable to be used in an analysis, generate basic reports showing the results. Prerequisites: STAT 820 or equivalent (SAS Certified BASE programmer for SAS or at least one year of experience as a data analyst/programmer). LEC.

The class is not offered for the Fall 2017 semester.

STAT 823 Introduction to Programming and Applied Statistics in R
This course will provide students with the opportunity to learn advanced statistical programming. The development of new statistical or computational methods often implies the development of programming codes to support its application. Much of this type of development is currently carried out in the R (or S-Plus) language. Indeed much of the recent development of statistical genetics is based on the R programming language and environment. This course provides an introduction to programming in the R language and it's applications to applied statistical problems. Prerequisites: Some previous exposure to computer programming. Some basic statistics at the Applied Regression or Applied Design level and permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 825 Nonparametric Methods
This course is an introduction to nonparametric statistical methods for data that doe not satisfy the normality or other usual distributional assumptions. We will cover most of the popular nonparametric methods used for different scenarios, such as a single sample, two independent or related samples, three or more independent or related samples, goodness-of-fit tests, and measures of association. Power and sample size topics will also be covered. The course will cover the theoretical basis of the methods at an intermediate mathematical level, and will also present applications using real world data and statistical software. Prerequisite: Permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 830 Experimental Design
The emphasis of this course is on learning the basics of experimental design and the appropriate application and interpretation of statistical analysis of variance techniques. Prerequisite: Permission of instructor, STAT 820 recommended. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Koestler, Devin
APPT- ONLNE KUEC - EDWARDS-K
3 25957

STAT 833 Sampling Methods
Students will be introduced to the design and analysis techniques when sampling from finite populations using simple, stratified, multistage, systematic, and complex sampling designs. Prerequisites: STAT 830 and STAT 872 or by permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 840 Linear Regression
This course is an introduction to model building using regression techniques. We will cover many of the popular topics in linear regression including: simple linear regression, multiple linear regression, model selection and validation, diagnostics, and remedial measures. Throughout the semester, we will be utilizing primarily SAS. Prerequisite: Permission of Instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Wick, Jo
APPT- ONLNE KUEC - EDWARDS-K
3 22837

STAT 845 Survival Analysis
This course provides an understanding of both the mathematical theory and practical applications for the analysis of time to event data with censoring. This includes univariate analysis, group comparisons, and regression techniques for survival analysis. Parametric and semi-parametric regression techniques covered will include those with categorical and/or continuous explanatory variables, both with and without interaction effects. Prerequisites: STAT 820, 835, 840, and 871, or by permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 850 Multivariate Statistics
This course will introduce the theory and methods of applied multivariate analysis. Topics include multivariate model formulation, multivariate normal distribution, Hotelling's T-square, multivariate analysis of variance, repeated measures analysis of variance, growth curves, discriminant analysis, classification analysis, principal components analysis, and cluster analysis. Computer exercises will be performed using SAS. Prerequisites: Knowledge of basic matrix algebra, STAT 820, STAT 840, and STAT 830. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Keighley, John
APPT- ONLNE KUEC - EDWARDS-K
3 24647

STAT 855 Statistical Methods in Genomics Research
This survey course will provide a high-level introduction to various statistical and bioinformatics methods involved in the study of biological systems. In particular, this course will provide an overview of the analytical aspects involved in: the study DNA, RNA, and DNA methylation data measured from both microarray and next-generation sequencing (NGS) technologies. This course will be held in a block format with 4 hours of lectures a day for two weeks (one week in June and one week in July), with readings and homework assignments assigned throughout the summer semester. During the last week of the summer semester, students will be required to participate in a group seminar session in which they will present the results from their assigned genomics projects. Prerequisite: STAT 820 Statistical Computing OR experience programming in a higher level programming language; STAT 840 Linear Regression; OR by permission of the instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 871 Mathematical Statistics
This course introduces the fundamentals of probability theory, random variables, distribution and density functions, expectations, transformations of random variables, moment generating functions, convergence concepts, sampling distributions, and order statistics. Prerequisite: Permission of Instructor. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Jayawardhana, Ananda
APPT- ONLNE KUEC - EDWARDS-K
3 22838

STAT 872 Mathematical Statistics II
This course introduces the fundamentals of statistical estimation and hypothesis testing, including point and interval estimation, likelihood and sufficiency principles, properties of estimators, loss functions, Bayesian analysis, and asymptotic convergence. Prerequisite: STAT 871 or by permission of instructor. LEC.

The class is not offered for the Fall 2017 semester.

STAT 880 Data Mining and Analytics
Students will be introduced to common steps used in data mining, such as assessing and assaying prepared data; pattern discovery; predictive modeling using decision trees, regression, and neural networks; and model assessment methods. Prerequisites: STAT 820, 830, 835, 840, and 871, or by permission of instructor. STAT 821 and 850 recommended. LEC.
Fall 2017
Type Time/Place and Instructor Credit Hours Class #
LEC Keighley, John
APPT- ONLNE KUEC - EDWARDS-K
3 25958

 

 

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