Distance Courses Currently Offered
For those with limited background in math, stats, and computing
- Statistics 531: Survey of Statistical Methods I
Univariate and bivariate data collection and organization, statistical estimation and hypothesis testing; analysis of relationships for categorical and numerical data, including Chi-square tests and simple linear and quadratic regression. Use of computing facilities required (SPSS statistical software). Prereq: 1 yr. college mathematics. - Statistics 532: Survey of Statistical Methods II
Multiple linear regression, including use of dummy variables; single and multiple factor analysis of variance and covariance; issues in experimental design and analysis. Use of computing facilities required. Prereq: 531.
For more technically oriented students
- Statistics 560: Introduction to Mathematical Statistics
Probablility, probability distributions, simulation of random variables, sampling distributions, central limit theorem, testing of hypotheses, confidence intervals, maxium liklihood methods, Bayesian methods. - Statistics 567: Analysis of Lifetime Data
Statistical analysis of lifetime data. Methods of analysis for complete and censored data. Lifetime data regression. Planning and analysis of life tests. Prereq: 563 or Mathematics 425 or consent of instructor. - Statistics 571: Statistical Methods
Applied statistical methods: estimation, tests of hypotheses, analysis of variance, nonparametric methods. Prereq: One year of calculus and one course in statistics. Uses JMP statistical software. - Statistics 572: Applied Regression Analysis
Simple linear regression. Matrix approach to multiple linear regression. Partial and sequential sums of squares, interaction and confounding, use of dummy variables, model selection. Leverage, influence and collinearity. Autocorrelated errors. Generalized linear models, maximum likelihood estimation, logistic regression, analysis of deviance. Nonlinear models, inference, ill-conditioning. Robust regression, M-estimators, iteratively reweighted least squares. Nonparametric regression, kernel, splines, testing lack of fit. Prereq: 571 and matrix algebra. - Statistics 573: Design of Experiments
One-way ANOVA, multiple range tests, equal and unequal variances, transformations; factorial experiments, completely randomized designs, analysis of covariance, split-plot and nested designs, fractional factorials, sequential designs. Prereq: 571. - Statistics 574: Data Mining
Understanding and application of data mining methods. Data preparation; exploratory data analysis and visualization; cluster analysis; logistic regression; decision trees; neural networks; association rules; model assessment; and other topics. Applications to real world data. Use of standard computer packages. Prereq: Stat 532 or Stat 538 or Stat 571, or consent of instructor. - Statistics 579: Applied Multivariate Methods
Multivariate techniques: Hotelling's T-sq., MANOVA, discriminant analysis, canonical correlation, principal component analysis, and factor analysis. Computer oriented approach: analysis and interpretation. Knowledge of basic matrices and SAS essential. Prereq: 538 or knowledge of regression and analysis of variance.
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(865) 974-2556
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(865) 974-2490
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