STATISTICS (ST)

NOTE: ST 175 and ST 275 both use appropriate software as an integral part of the course.

ST 175 Basic Statistics 4 cr
Frequency distributions and representations, measures of central tendency, dispersion, and relative standing, probability, binomial and normal distributions, sampling and sampling distributions, parametric estimation and hypothesis testing, large- and small-sample applications. Prerequisite: High-school-level algebra.

ST 275 Statistical Methods 4 cr
Continuation of ST 175. Estimation and hypothesis testing, experimental design and analysis of variance, distribution-free methods, contingency tables, correlation, simple linear, polynomial, and multiple linear regression, model-building procedures, computer-assisted data analysis using appropriate computer software. See "To Avoid Duplication." Prerequisites: ST 175 and the equivalent of MA 171.

ST 280 Sampling and Survey Techniques 4 cr
Sampling concepts and designs for survey investigations. Probability sampling techniques to include simple random, stratified, one- and two-stage cluster, and systematic, sample-size determination, ratio and regression estimation, random response modeling, introduction to acceptance sampling. Prerequisite: ST 175 or equivalent.

ST 290 Special Topics 1-4 cr
Selected topics in elementary undergraduate applied statistics.

ST 315 Statistical Analysis 5 cr
Intended for students in engineering, mathematics, and the mathematical and physical sciences. Probability distributions, descriptive treatment of data, sampling distributions, estimation and hypothesis testing, experimental design and analysis of variance, correlation analysis, simple, polynomial, and multiple regression analysis, computer-assisted data analysis using appropriate computer software. See "To Avoid Duplication." Prerequisite: MA 132 or 278.

ST 334 Statistical Computing 4 cr
An introduction to computer-assisted data analysis with emphasis on the interpretation of output generated by appropriate computer software, including SPSSX and SAS. Coverage includes descriptive statistics, contingency tables, two-group comparisons, simple, polynomial and multiple linear regression, correlation, and analysis of variance. Prerequisite: ST 275 or 315.

ST 337 Applied Regression Analysis 4 cr
Least squares simple, polynomial, and multiple linear regression including residual and lack-of-fit analysis, simple, multiple, partial, and multiple-partial correlations, analysis of covariance, model-building algorithms, analysis of variance including unequal cell replication, computer-assisted data analysis using appropriate computer software. Prerequisite: ST 275 or 315.

ST 347 Applied Time Series Analysis 4 cr
Fundamentals concepts; exponential smoothing stationary and nonstationary models; moving average, autoregressive, and ARIMA processes; estimation of ARIMA models; forecasting processes; Box-Jenkins methodology; applications. Prerequisite: ST 275 or 315.

ST 352 Nonparametric Statistics 4 cr
Distribution-free analysis of location and scale measures, association and contingency table analysis, nonparametric goodness-of-fit procedures and tests of randomness. Prerequisite: ST 275 or 315.

ST 356 Design and Analysis of Experiments I 4 cr
Principles, construction, and analysis of experimental designs to include completely randomized, randomized complete block, latin square, graeco latin square, split plot and split-split plot, multiple comparison analysis, expected mean squares, factorial experimentation, designs with nested and/or crossed factors. Prerequisite: ST 275 or 315.

ST 361 Survival Data Analysis 4 cr
Statistical applications to time-dependent responses as applied to survival and life-testing data. Definitions and properties of survival distributions. Parametric and nonparametric methods of estimating and comparing survival distributions. Identification of prognostic factors related to survival time and response. Concepts, rationale, and design of clinical trials. Sample size determinations. Prerequisite: ST 352.

ST 444 Statistical Quality Control 4 cr
Probability distributions in quality control, inferences about process quality, control charts for attributes and variables, process capability analysis, economic design of control charts, acceptance sampling by attributes and variables, standard-sampling strategies (MIL-STD-1050D, Dodge-Romig, MIL-STD-414), economic design of sampling plans, applications. Prerequisite: ST 275 or ST 315.

ST 448 Applied Reliability and Life Testing 4 cr
Reliability concepts, censoring, reliability distributions, estimation and hypothesis testing, data plotting, goodness-of-fit, Kaplan-Meier estimation, physical acceleration models, Cox's proportional hazard model, series and parallel systems models, burn-in models, computer-assisted data analysis. Prerequisite: ST 275.

ST 452 Categorical Data Analysis 4 cr
Analysis of two-way, three-way, and higher dimension contingency tables using log-linear models; measures of association for nominal and ordinal tables; logistic regression; weighted least squares analysis. Prerequisites: ST 334 and 337.

ST 456 Design and Analysis of Experiments II 4 cr
Continuation of ST 455, Incomplete block designs, analysis of covariance, regression approach to the analysis of selected designs including two-way unequal cells, factorial confounding techniques, fractional replication, response surface methodology, evolutionary operations, cross-over and repeated measures designs, selected transformations and heterogeneity of variance techniques. Prerequisites: ST 337 and 356.

ST 467 Multivariate Statistical Analysis 4 cr
Multivariate normal distribution, sampling distributions, hypothesis testing, principal components and introduction to factor analysis, canonical correlation analysis, discriminant and classification analysis, MANOVA. Prerequisite: ST 337.

ST 468 Advanced Statistical Computing 4 cr
Computer-assisted data analysis using SPSSX, SAS, and selected specialized statistical software. Coverage includes factorial unequal-cell analysis, discriminant and classification analysis, principal components and factor analysis, canonical correlation, MANOVA, advanced multiple regression analysis. Prerequisites: ST 334 and 467.

ST 471 Theory of Statistics I 4 cr
A comprehensive introduction to statistical distributions and their characterizations, generating functions, conditional expectations, order statistics, sampling distributions, convergence concepts, maximum likelihood and moment estimation, properties of estimators, confidence intervals. Prerequisite: MA 451.

ST 472 Theory of Statistics II 4 cr
Comprehensive introduction to statistical hypothesis testing, uniformly most powerful tests, likelihood ratio tests, chi-square tests, analysis of variance, regression, nonparametric theory, decision theory, sequential testing. Prerequisite: ST 471.

ST 481 Statistical Practicum (W) 2 cr
Relates the student's classroom studies with actual statistical problems encountered in practice. Working with the departmental statistical consultant, the student will participate in providing statistical assistance to research faculty in applied fields. Prerequisites: Senior standing and permission of the department chair.

ST 490 Special Topics 1-4 cr
Selected topics in advanced undergraduate applied statistics. This course may be repeated for a maximum of nine credits.

ST 494 Directed Studies 1-4 cr
Directed study. Prerequisite: Permission of the department chair. May be repeated for credit up to a maximum of eight credits.

ST 540 Statistical Research Methods I 4 cr
A service course for graduate students in disciplines other than mathematics and statistics. A non-calculus exposition in support of application. Coverage includes descriptive statistics, probability and probability distributions, sampling, estimation, tests of significance, analysis of variance, correlation, linear regression, nonparametric procedures, contingency table analysis, and computer-assisted data analysis using appropriate computer software.

ST 541 Statistical Research Methods II 4 cr
Continuation of ST 540. Coverage includes polynomial and multiple linear regression including residual and lack-of-fit analysis; multiple, partial and multiple-partial correlation analysis; model building algorithms; model comparisons using dummy variables; analysis of covariance; completely randomized, randomized complete block, and factorial experimentation for equal and unequal cell replication; binary response modeling; computer-assisted data analysis using SPSSX and SAS. Prerequisite: ST 540 or equivalent.

Courses of Instruction

Bulletin Home Page

USA Home