Course Descriptions: Academics: School of Science: Indiana University Indianapolis

STAT-S 639 - Multilevel Models

Credits:: 3
Description:: Introduction to the general multilevel model with an emphasis on applications. Discussion of hierarchical linear models, and generalizations to nonlinear models. How such models are conceptualized, parameters estimated and interpreted. Model fit via software. Major emphasis throughout the course will be on how to choose an appropriate model and computational techniques. Equivalent to EDUC Y639.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 640 - Multivariate Data Analysis

Credits:: 3
Description:: Elementary treatment of multivariate normal distributions, classical inferential techniques for multivariate normal data, including Hotelling’s T² and MANOVA. Discussion of analytic techniques such as principal component analysis, canonical correlation analysis, discriminant analysis, and factor analysis. Equivalent to PSY P654.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 645 - Covariance Structure Analysis

Credits:: 3
Description:: Path analysis. Introduction to multivariate multiple regression, confirmatory factor analysis, and latent variables. Structural equation models with and without latent variables. Mean-structure and multi-group analysis. Equivalent to EDUC Y645.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 650 - Time Series Analysis

Credits:: 3
Description:: Techniques for analyzing data collected at different points in time. Probability models, forecasting methods, analysis in both time and frequency domains, linear systems, state-space models, intervention analysis, transfer function models and the Kalman filter. Stationary processes, autocorrelations, partial autocorrelations, autoregressive, moving average, and ARMA processes, spectral density of stationary processes, periodograms, estimation of spectral density. Course equivalent to MATH M568.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 655 - Longitudinal Data Analysis

Credits:: 3
Description:: Introduction to methods for longitudinal data analysis; repeated measures data. The analysis of change—models for one or more response variables, possibly censored. Association of measurements across time for both continuous and discrete responses. Course is equivalent to EDUC Y655.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 660 - Sampling

Credits:: 3
Description:: Design of surveys and analysis of sample survey data. Simple random sampling, ratio and regression estimation, stratified and cluster sampling, complex surveys, nonresponse bias.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 670 - Exploratory Data Analysis

Credits:: 3
Description:: Numerical and graphical techniques for summarizing and displaying data. Exploration versus confirmation. Connections with conventional statistical analysis and data mining. Applications to large data sets.
Prerequisite:: Two statistics courses at the graduate level, or consent of instructor.

STAT-S 675 - Statistical Learning and High-Dimension Analysis

Credits:: 3
Description:: Dataanalytic methods for exploring the structure of high-dimensional data. Graphical methods, linear and nonlinear dimension reduction techniques, manifold learning. Supervised, semisupervised, and unsupervised learning.
Prerequisite:: STAT S640, or two statistics courses at the graduate level, or consent of instructor.

STAT-S 681 - Topics in Applied Statistics

Credits:: 3
Description:: Careful study of a statistical topic from an applied perspective.
Prerequisite:: Consent of instructor.

STAT-S 682 - Topics in Mathematical Statistics

Credits:: 3
Description:: Careful study of a statistical topic from a theoretical perspective.
Prerequisite:: Consent of instructor.

STAT-S 690 - Statistical Consulting

Credits:: 4
Description:: Development of effective consulting skills, including the conduct of consulting sessions, collaborative problem-solving, using professional resources, and preparing verbal and written reports. Interactions with clients will be coordinated by the Indiana Statistical Consulting Center (ISCC).
Prerequisite:: Consent of instructor.

STAT-S 692 - Internship in Statistical Consulting

Credits:: 3
Description:: One semester internship at the Indiana Statistical Consulting Center (ISCC). Students work on actual consulting problems under the direct supervision of professional statisticians.
Prerequisite:: STAT S690 and permission of Director of Graduate Studies.

STAT-S 695 - Readings in Statistics

STAT 69500 - Seminar in Mathematical Statistics

Credits:: 1
Description:: Individual study that meets 3 times per week for 50 minutes per meeting for 16 weeks.
Prerequisite:: Consent of advisor.

STAT-I 698 - Research M.S. Thesis

STAT-S 710 - Statistical Computing

Credits:: 3
Description:: Survey of numerical methods in statistics. Matrix factorizations and algorithms for linear regression. Nonlinear optimization, maximum likelihood and nonlinear regression. Pseudorandom number generation and Monte Carlo methods.
Prerequisite:: STAT S620, or consent of instructor.

STAT-S 721 - Advanced Statistical Theory I

Credits:: 3
Description:: Mathematical introduction to major areas of statistical theory and practice, including statistical models, sufficiency, likelihood inference, estimation and testing, Bayesian inference, decision theory, equivariance, and optimality of test statistics.
Prerequisite:: S620, some knowledge of elementary measure theory, and/or consent of the instructor.

STAT-S 722 - Advanced Statistical Theory II

Credits:: 3
Description:: A continuation of S721. A mathematical introduction to major areas of statistical theory and practice including multinomial models, canonical linear models, exponential families, asymptotic theory, and general linear models.
Prerequisite:: S721 or consent of the instructor.

STAT-S 730 - Theory of Linear Models

Credits:: 3
Description:: Theory of the general linear model. Distribution theory, linear hypotheses, the Gauss-Markov theorem, testing and confidence regions. Application to regression and to analysis of variance.
Prerequisite:: STAT S620, or consent of instructor.

STAT-S 740 - Multivariate Statistical Theory

Credits:: 3
Description:: Multivariate normal distributions. Multivariate linear normal models, estimation and testing. Wishart distributions and models. Inference for the covariance matrix. Eigenvalues, including canonical correlations and principal components/factor analysis.
Prerequisite:: STAT S721 and S722, or consent of the instructor.

Course Descriptions