Department of Mathematical Sciences, College of Arts and Sciences
Graduate Courses in Statistics (STT)
Additional offerings by the department include courses in Mathematics (MAT)
Mark Ginn, Department Chair
STT 5530-5549. Selected Topics (1-4).On Demand.
STT 5811. Statistical Concepts and Applications I (3).F. This course introduces students at the post-calculus level to statistical concepts, applications, and theory. Topics include: counting methods, basic probability, sampling methods, an introduction to the most common discrete and continuous random variables, sampling distributions, and single parameter inferential methods including confidence intervals and hypothesis testing using large-sample methods, exact methods, and computationally intensive methods such as the bootstrap. Statistical concepts will be developed through simulations, and applications will focus on statistical problem-solving. The course will introduce prospective college teachers to the content and pedagogy recommended in the American Statistical Association’s Guidelines with regard to statistics and probability. Prerequisites: MAT 1120 (Calculus with Analytic Geometry II) and STT 2810 (Introduction to Statistics) or equivalent course.
STT 5812. Statistical Concepts and Applications II with Probability Modeling (3).S. This course is a continuation of STT 5811. Topics include: an introduction to the design of experiments, exploring and modeling relationships between variables, including chisquare analysis, regression models, ANOVA, and logistic regression. Inferential procedures for each of these models will also be covered. Computationally intensive methods, such as permutation tests, will also be introduced. Statistical concepts will be developed through simulations, and applications will focus on statistical problem-solving and appropriate communication of results of a statistical analysis. Students will use two or more statistical software packages during the course. The goal of the course is to provide sufficient theory and methodology to prepare students to teach the introductory level statistics course. Prerequisite: STT 5811 or permission of instructor.
STT 5820. Design and Analysis of Experiments (3).On Demand. The course begins with a review of sampling, sampling distributions, and simple comparative experiments. Single factor experiments with both fixed and random effects are considered. Designs illustrated include randomized blocks, latin squares and factorial experiments. Mixed models and rules for expected mean square are presented. Model adequacy, sample size considerations, power determinations and restrictions on randomization procedures are discussed. The use of statistical software packages is integrated throughout the course. Prerequisite: STT 3820 (Statistical Methods I), or permission of the instructor. [Dual-listed with STT 4820.]
STT 5830. Linear Regression Models (3).F. An introduction to least squares estimation in simple and multiple regression models. The matrix approach is used in the more general multiple regression model. Considerable attention is given to the analysis of variance, aptness of the model tests, residual analysis, the effects of multicollinearity, and variable selection procedures. Prerequisites: MAT 2240 (Intro to Linear Algebra) and STT 3830 (Statistical Methods II) or equivalent. [Dual-listed with STT 4830.]