Courses for Advanced Undergraduates & Graduate Students

551 Introduction to Probability (3:3)

Pr. grade of at least C in STA 290 and MAT 293 or permission of instructor

Events and probabilities (sample spaces), dependent and independent events, random variables and probability distribution, expectation, moment generating functions, multivariate normal distribution, sampling distributions. (Fall)

552 Introduction to Mathematical Statistics (3:3)

Pr. grade of at least C in STA 551 or permission of instructor

Point estimation, hypothesis testing, confidence intervals, correlation and regression, small sample distributions. (Spring)

562 Statistical Computing (3:3)

Pr. STA 291 or 580 and knowledge of a scientific programming

language

Statistical methods requiring significant computing or specialized software. Simulation, randomization, bootstrap, Monte Carlo techniques; numerical optimization. Extensive computer programming involved. This course does not cover the use of statistical software packages. (Alt Fall)

565 Analysis of Survival Data (3:3)

Pr. STA 291 or 352 or permission of instructor

Methods for comparing time-to-event data, including parametric and nonparametric procedures for censored
or truncated data, regression model diagnostics, group comparisons, and the use of relevant statistical
computing packages. (Alt)

571 Statistical Methods for Research I (3:3)

Coreq. 571L

Hours do not count toward degree requirements for a mathematics major.

Introduction to statistical concepts. Basic probability, random variables, the binomial, normal and Student’s t distributions, hypothesis tests, confidence intervals, chi-square tests, introduction to regression, and analysis of variance. (Fall)

571L Statistical Methods Laboratory I (1:0:2)

Coreq. 571

Hours do not count toward degree requirements for a mathematics major.

Using statistical software packages for data analysis. Problems parallel assignments in 571. (Fall)

572 Statistical Methods for Research II (3:3)

Pr. 571 and 571L or permission of instructor

Coreq. 572L

Statistical methodology in research and use of statistical software. Regression, confidence intervals, hypothesis testing, design and analysis of experiments, one- and two-factor analysis of variance, multiple comparisons, hypothesis tests. (Spring)

572L Statistical Methods Laboratory II (1:0:2)

Pr. 571 and 571L or permission of instructor

Coreq. 572

Using statistical software packages for data analysis. Problems parallel assignments in 572. (Spring)

573 Theory of Linear Regression (3:3)

Pr. grade of at least C in 352 and MAT 310, or 662, or permission of instructor

Linear regression, least squares, inference, hypothesis testing, matrix approach to multiple regression. Estimation, Gauss-Markov Theorem, confidence bounds, model testing, analysis of residuals, polynomial regression, indicator variables. (Fall)

574 Theory of the Analysis of Variance (3:3)

Pr. grade of at least C in 573 or permission of instructor

Multivariate normal distribution, one-way analysis of variance, balanced and unbalanced two-way analysis of variance, empty cells, multiple comparisons, special designs, selected topics from random effects models. (Spring)

575 Nonparametric Statistics (3:3)

Pr. grade of at least C in 352 or 572 or 662, or permission of instructor

Introduction to nonparametric statistical methods for the analysis of qualitative and rank data. Binomial test, sign test, tests based on ranks, nonparametric analysis of variance, nonparametric correlation and measures of association. (Fall)

580 Biostatistical Methods (3:3)

Pr. grade of at least C in STA 271 or STA 290 or permission of instructor

Statistical methods for biological research including: descriptive statistics; probability distributions; parametric and nonparametric tests; ANOVA; regression; correlation; contingency table analysis. (Fall)

581 SAS System for Statistical Analysis (1:1)

Pr. STA 271, 290, or similar introductory statistics course

Creating, importing, and working with SAS data sets. Using SAS procedures for elementary statistical analysis, graphical displays, and report generation. (Fall & Spring)

593, 594 Directed Study in Statistics (1–3), (1–3) (Fall & Spring)

Please refer to The Graduate School Bulletin

for additional graduate-level courses.