Using statistics in your profession is an exciting and important aspect to your career development. Our courses offer you the opportunity to learn how to apply statistics to real problems.

In addition to our core courses, we offer several courses specifically for those interested in applied statistics.

See our Course Listing page for additional information.

Sampling

STAT 607 – Planning, execution, and analysis of sampling from finite populations; simple, stratified, multistage, and systematic sampling; ratio estimates.

Multivariate Analysis

STAT 636 – Multivariate extensions of the chi-square and t-tests, discrimination and classification procedures. Applications to diagnostic problems in biological, medical, anthropological, and social research; multivariate analysis of variance, principal component and factor analysis, canonical correlations.

Bayesian Methods

STAT 638 – Students learn how uncertainty regarding parameters can be explicitly described as a posterior distribution which blends information from a sampling model and prior distribution. Students are exposed to foundational principles, but the course emphasizes modeling and computations under the Bayesian paradigm.

Spatial Statistics

STAT 647 – Spatial correlation and its effects; spatial prediction (kriging); spatial regression; analysis of point patterns (tests for randomness and modelling patterns); subsampling methods for spatial data.

Stats in Research III

STAT 653 – The analysis of messy and complex data sets using analysis of variance, analysis of covariance and regression analysis. Transformations; regression diagnostics; nonlinear, robust, logistic and principal components regression; structural equations.

Applied Analytics

STAT 656 – Applied Analytics Using SAS Enterprise Miner:  Introduction to data mining and will demonstrate the procedures; Optimal prediction decisions; comparing and deploying predictive models; neural networks; constructing and adjusting tree models; the construction and evaluation of multi-stage models. NOTE: For this course, you will be required to have a computer with a Windows OS and good processing power.

Advanced SAS Programming

STAT 657 – Programming with SAS/IML, programming in SAS Data Step, advanced use of various SAS procedures.

Categorical Data Analysis

Introduction to analysis and interpretation of categorical data using ANOVA/regression analogs; includes contingency tables, loglinear models, logistic regression; use of computer software such as SAS, GLIM, SPSSX.