This is an independent study project, topic to be selected in consultation with the instructor. Purpose is to integrate all materials learned in the program and apply these principles to the solution of an actual problem in biomedical engineering technology. Prerequisites: Permission of instructor and completion of year 1 PBME studies.
BST 535 provides an introduction to R programming with an emphasis on exploration, manipulation, and visualization of data sets. Students will learn application of statistical techniques in R, statistical programming, and practice effective communication of one's findings.
BST 631 covers design and analysis issues associated with well-known national health surveys, including reliability and validity of measurements, instrument validation, sampling designs, weighting of responses, and multiple imputations. Students will learn how to use statistical software to analyze data from complex survey designs.
BST 635 covers basic concepts on databases with applications to public health. Students will learn how to program in SAS, the leading statistical analysis system. SAS skills include managing data, using SQL, generating descriptive statistics, visualizing data, writing reports, writing MACROs, and programming using SAS.
BST 636 covers statistical techniques for issues associated with the exploration of large public health data sets and the development of models from such data sets. The practical issues involved in analyzing large observational healthcare data will be addressed with a focus on appropriate interpretations and the effective communication of results.
BST 662 presents applied statistical techniques for analyzing data from longitudinal studies and repeated measures experiments that occur frequently in public health, clinical and translational trials, and health outcomes research. This course will cover linear mixed models, generalized linear mixed models and generalized estimating equations as they apply to the analysis of correlated data.
BST 699 provides advanced practice in team science for biostatisticians working in public health or biomedical research. In this hands-on, experiential course, students apply their knowledge of written and oral communication strategies to effectively collaborate with other scientists.
Surgical, dental implant education has increasingly become part of predoctoral dental curricula. This course will integrate innovative technology in dental implant therapy to provide various treatment modalities in an interdisciplinary setting. Students will learn basic surgical concepts and principles related to fully guided implant surgery, including minimally traumatic extraction with ridge preservation, digital impressions for virtual treatment planning, surgical placement of the fully guided implant, and complete digital workflow for implant restorations.
This course introduces students to sustainability and its connection to civil engineering infrastructure. Course topics are divided into environmental, economic, and social sustainability and include life cycle assessment, water and waste management, life cycle costing and techno-economic assessment, applying empathy in engineering, quantitative approaches for social sustainability, and decision-making across sustainability metrics.
Design of structural steel connections, beam bearing plates, column base plates, beams including lateral-torsional buckling, composite beams, and frame stability.
