| Stat 525 [ 3 ] SAS Programming |
| Description: A detailed introduction to the SAS programming language. Topics covered include reading data, storing data, manipulating data, data presentation, graphing, and macro programming. SAS software will be used. |
| Prerequisite: Stat 345, 427 |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 35546 |
Stat 525 001 |
W |
1730-2000 |
ESCP |
|
Sorell, M.
|
|
|
| Stat 527 [ 3 ] Advanced Data Analysis I |
| Description: Statistical tools for scientific research, including parametric and non-parametric methods for ANOVA and group comparisons, simple linear and multiple linear regression and basic ideas of experimental design and analysis. Emphasis placed on the use of statistical packages such as Minitab and SAS. Course cannot be counted in the hours needed for graduate degrees in Mathematics and Statistics. |
| Prerequisite: Stat 145 |
| Semesters offered: Fall |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| |
Stat 527 001 |
MWF |
1100-1150 |
ANTHO |
|
Cancelled, .
|
| AOA Stat 427-001 |
|
|
|
|
|
| |
Stat 527 002 |
MWF |
1400-1450 |
DSH |
|
Cancelled, .
|
| AOA Stat 427-002 |
|
|
|
|
|
| 35813 |
Stat 527 003 |
TR |
1100-1215 |
DSH |
|
Christensen, R.
|
|
|
| Stat 528 [ 3 ] Advanced Data Analysis II |
| Description: A continuation of 527 that focuses on methods for analyzing multivariate data and categorical data. Topics include MANOVA, principle components, discriminant analysis, classification, factor analysis, analysis of contingency tables including log-linear models for multidimensional tables and logistic regression. |
| Prerequisite: 527 |
|
| Stat 531 [ 3 ] Statistical Genetics I |
| Description: A detailed examination of the statistical methods used in analyzing genetic data. Topics covered include the estimation of allele frequencies, testing for Hardy-Weinberg equilibrium, classical and complex segregation analysis, linkage analysis for Mendelian and complex diseases, and the detection of allelic association. Popular genetic software will be used for data analysis. |
| Prerequisite: Stat 345, 427 |
| Semesters offered: Alternate Falls |
|
| Stat 532 [ 3 ] Statistical Genetics II |
| Description: A continuation of 531. Topics covered include statistical methods for describing variation in quantitative traits, methods of mapping and characterizing quantitative trait loci and other current topics in statistical genetics, including the analysis of microarray data and phylogenetic methods. Popular genetic software will be used for data analysis. |
| Prerequisite: Stat 531 |
| Semesters offered: Alternate Springs |
|
| Stat 534 [ 3 ] Contingency Tables & Dependence Structures |
| Description: This course examines the use of log-linear models to analyze count data. It also uses graphical models to examine dependence structures for both count data and measurement data. |
| Prerequisite: Stat 345 and 527 |
|
| Stat 538 [ 3 ] Biostatistical Methods I for Public Health & Medical Sciences |
| Description: Covers basic statistical methods, including statistical summaries and inference. Methods of summarizing data include graphical displays and numerical summaries. Statistical inference includes hypothesis testing and confidence intervals. Methods for continuous and categorical data are studied. |
| Prerequisite: B or better in Math 121 |
| Semesters offered: Fall |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 13810 |
Stat 538 001 |
TR |
0930-1130 |
SOM2 |
|
Guindani, M.
|
|
|
| Stat 539 [ 3 ] Biostatistical Method II for Public Health & Medical Sciences |
| Description: Covers basic models used in the statistical analysis of studies in the medical sciences and public health field, with an emphasis on epidemiology. Linear regression, analysis of variance, logistic regression, and survival models are studied. |
| Prerequisite: Stat 538 |
| Semesters offered: Spring |
|
| Stat 540 [ 3 ] Regression Analysis |
| Description: Simple regression and multiple regression. Residual analysis and transformations. Matrix approach to general linear models. Model selection procedures, nonlinear least squares, logistic regression. Computer applications. |
| Prerequisite: 527 |
| Semesters offered: Fall |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 13814 |
Stat 540 001 |
TR |
1230-1345 |
DSH |
|
Storlie, C.
|
| AOA Stat 440 |
|
|
|
|
|
|
|
| Stat 545 [ 3 ] Analysis of Variance and Experimental Design |
| Description: A data-analytic course. Multifactor ANOVA. Principles of experimental design. Analysis of randomized blocks, Latin squares, split plots, etc. Random and mixed models. Extensive use of computer packages with interpretation, diagnostics. |
| Prerequisite: 540 |
| Semesters offered: Spring |
|
| Stat 546 [ 3 ] Theory of Linear Models |
| Description: Theory of the Linear Models discussed in 440/540 and 445/545. Linear spaces, matrices, projections, multivariate normal distribution and theory of quadratic forms. Non-full rank models and estimability. Gauss-Markov theorem. Distribution theory for normality assumptions. Hypothesis testing and confidence regions. |
| Prerequisite: Stat 553, 545, linear algebra |
| Semesters offered: Alternate Falls |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 33793 |
Stat 546 001 |
TR |
1400-1515 |
HUM |
|
Christensen, R.
|
|
|
| Stat 547 [ 3 ] Multivariate Analysis & Advanced Linear Models |
| Description: Hotelling T2, multivariate ANOVA and Regression, classification and discrimination, principal components and factor analysis, clustering, graphical and computational techniques, topics in linear models. |
| Prerequisite: Stat 546 |
| Semesters offered: Alternate Springs |
|
| Stat 553 [ 3 ] Statistical Inference with Applications |
| Description: Transformations of univariate and multivariate distributions to obtain the special distributions important in statistics. Concepts of estimation and hypothesis testing in both large and small samples with emphasis on the statistical properties of the more commonly used procedures, including Students t-tests, F-tests and chi-square tests. Confidence intervals. Performance of procedures under non-standard conditions (i.e., robustness). |
| Prerequisite: Stat 561 |
| Semesters offered: Spring |
|
| Stat 556 [ 3 ] Advanced Statistical Inference I |
| Description: Theory and methods of point estimation, sufficiency and its applications. |
| Prerequisite: Stat 553, 561 and Math 510. |
| Semesters offered: Alternate Falls |
|
| Stat 557 [ 3 ] Advanced Statistical Inference II |
| Description: Standard limit theorems, hypothesis testing, confidence intervals and decision theory. |
| Prerequisite: Stat 556 |
| Semesters offered: Alternate Springs |
|
| Stat 561 [ 3 ] Probability |
| Description: (Also offered as MATH 441.) Mathematical models for random experiments, random variables, expectation. The common discrete and continuous distributions with application. Joint distributions, conditional probability and expectation, independence. Laws of large numbers and the central limit theorem. Moment generating functions. |
| Prerequisite: Math 264 |
| Semesters offered: Fall |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 13819 |
Stat 561 001 |
TR |
1400-1515 |
ORTG |
|
Guindani, M.
|
| AOA Stat 461, Math 441 |
|
|
|
|
|
|
|
| Stat 562 [ 3 ] Intermediate Probability |
| Description: Multivariate distributions and densities, transformations of random vectors, special multivariate distributions including the normal and multinominal, limit theorems for sequences of random variables, and topics from stochastic processes including random walks, Markov chains, Poisson processes, and Brownan motion. |
| Prerequisite: 561 |
| Semesters offered: Spring |
|
| Stat 565 [ 3 ] Stochastic Processes with Applications |
| Description: Markov chains and processes with applications. Classification of states. Decompositions. Stationary distributions. Probability of absorption, the gambler's ruin and mean time problems. Queuing and branching processes. Introduction to continuous time Markov processes. Jump processes and Brownian motion. |
| Prerequisite: Stat 561 |
| Semesters offered: Offered Upon Demand |
|
| Stat 567 [ 3 ] Advanced Probability |
| Description: (Also offered as Math 541.) A measure theoretic introduction to probability theory. Construction of probability measures. Distribution and characteristic functions, independence and zero-one laws. Sequences of independent random variables, strong law of large numbers and central limit theorem. Conditional expectation. Martingales. |
| Prerequisite: Math 563 |
| Semesters offered: Alternate Springs |
|
| Stat 569 [ (3, n ] Selected Topics in Probability Theory |
| Description: (Credit: 3, no limit.) Also offered as Math 549. |
|
| Stat 570 [ 3 ] Industrial Statistics |
| Description: Basic ideas of statistical quality control and improvement. Topics covered: Demings 14 points and deadly diseases, Pareto charts, histograms, cause and effect diagrams, control charts, sampling, prediction, reliability, experimental design, fractional factorials, Taguchi methods, response surfaces. |
| Prerequisite: Stat 345 |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 33794 |
Stat 570 001 |
MWF |
1400-1450 |
DSH |
|
Zhang, G.
|
| AOA Stat 470 |
|
|
|
|
|
|
|
| Stat 572 [ 3 ] Sampling Theory and Practice |
| Description: Basic methods of survey sampling; simple random sampling, stratified sampling, cluster sampling, systematic sampling and general sampling schemes; estimation based on auxiliary information; design of complex samples and case studies. |
| Prerequisite: Stat 345 |
| Semesters offered: Alternate Falls |
|
| Stat 574 [ 3 ] Biostatistical Methods: Survival Analysis & Logistics Regression |
| Description: A detailed overview of methods commonly used to analyze medical and epidemiological data. Topics include the Kaplan-Meier estimate of the survivor function, models for censored survival data, the Cox proportional hazards model, methods for categorical response data including logistic regression and probit analysis, generalized linear models. |
| Prerequisite: 528 or 540 |
|
| Stat 576 [ 3 ] Multivariate Analysis |
| Description: Tools for multivariate analysis including multivariate ANOVA, principle components analysis, discriminant analysis, cluster analysis, factor analysis, structural equations modeling, canonical correlations and multidimensional scaling. |
| Prerequisite: 528 or 540 |
| Semesters offered: Offered Upon Demand |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 33795 |
Stat 576 001 |
TR |
0930-1045 |
DSH |
|
Storlie, C.
|
| AOA Stat 476 |
|
|
|
|
|
|
|
| Stat 577 [ 3 ] Introduction to Bayesian Modeling |
| Description: An introduction to Bayesian methodology and applications. Topics covered include: probability review, Bayes' theorem, prior elicitation, Markov chain Monte Carlo techniques. The free software programs WinBUGS and R will be used for data analysis. |
| Prerequisite: Stat 561 and (527 or 540). |
| Semesters offered: Alternate Springs |
|
| Stat 579 [ 3 (No ] Selected Topics in Statistics |
| Description: (Credit: 3, no limit.) |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| |
Stat 579 001 |
MWF |
1100-1150 |
REGH |
|
Cancelled, .
|
| Transition to Research |
|
|
|
|
|
| 35857 |
Stat 579 010 |
W |
1500-1730 |
CAST |
|
Brown, J.
|
|
|
| Stat 581 [ 3 ] Introduction to Time Series Analysis |
| Description: Introduction to time domain and frequency domain models of time series. Data analysis with emphasis on Box-Jenkins methods. Topics such as multivariate models; linear filters; linear prediction; forecasting and control. |
| Prerequisite: 561 |
| Semesters offered: Alternate Springs |
|
| Stat 582 [ 3 ] Advanced Time Series Analysis |
| Description: Time series models in the time and spectral domains. Linear filters. Multivariate models. Autoregressive and moving average models. Filtering and prediction. Distribution theory. Design of experiments. |
| Prerequisite: Stat 581
|
| Semesters offered: Alternate Falls |
|
| Stat 585 [ 3 ] Nonparametric and Robust Methods |
| Description: Statistical methods that are insensitive to the distribution of the data. Sign tests, Kolmogorov-Smirnov tests, rank tests including the Wilcoxon, Mann-Whitney, Kruskal-Wallis, and Friedman tests. Robust estimation including M estimators, L estimators and R estimators. |
| Prerequisite: 561 |
| Semesters offered: Offered Upon Demand |
|
| Stat 586 [ 3 ] Nonparametric Curve Estimation & Image Reconstruction |
| Description: Nonparametric regression, density estimation, filtering, spectral density estimation, image reconstruction and pattern recognition. Tools include orthogonal series, kernels, splines, wavelets and neural networks. Applications to medicine, engineering, biostatistics and economics. |
| Prerequisite: Stat 561 |
| Semesters offered: Offered Upon Demand |
|
| Stat 590 [ 3 ] Statistical Computing |
| Description: A detailed examination of essential statistical computing skills needed for research and industrial work. Students will use S-Plus, Matlab and SAS to develop algorithms for solving a variety of statistical problems using resampling and simulation techniques such as the bootstrap, Monte Carlo methods and Markov chain methods for approximating probability distributions. Applications to linear and non-linear models will be stressed. |
| Prerequisite: 528 |
|
| Stat 595 [ (1-3, ] Problems |
| Description: (Credit: 1-3, no limit.) |
|
| Stat 597 [ (1-3, ] Statistical Consulting Laboratory |
| Description: (Credit: 1-3, no limit.) Provides experience in statistical consulting and analysis of real data. |
| Prerequisite: 528 |
| Fall 2009 Class Schedule |
| Call # |
Course |
Days |
Time |
Bldg. |
Room |
Instructor |
| 13835 |
Stat 597 001 |
ARR |
|
|
|
Christensen, R.
|
|
|
| Stat 599 [ 1-6 ( ] Master's Thesis |
| Description: Offered on a CR/NC basis only. |
|
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