Residency credit for dissertation research after the qualifying examination. Students may register for this course in the semester of the qualifying examination. A minimum of two semesters are required as well as continuous enrollment (Fall and Spring) until the dissertation is completed and defended.
Individually directed research and reading in particular aspects of medical behavioral science under the supervision of one or more members of the faculty. May be repeated up to a maximum of 12 hours.
BST 230 provides students with an introduction to statistical concepts that are important for solving real-world public health problems. This course will present statistical principles and associated scientific reasoning underlying public health practice and health policy decision- making. Topics include data visualization, summary statistics, statistical inference, study design and data analysis, and strategies for articulating and evaluating claims using statistical constructs.
BST 230 provides students with an introduction to statistical concepts that are important for solving real-world public health problems. This course will present statistical principles and associated scientific reasoning underlying public health practice and health policy decision- making. Topics include data visualization, summary statistics, statistical inference, study design and data analysis, and strategies for articulating and evaluating claims using statistical constructs.
BST 600 covers basic statistical methods that are commonly encountered in health-related research. Major topics include descriptive statistics, estimation and hypothesis testing for means and proportions, correlation, and regression, with a special focus on the computation and interpretation of these methods for analyzing health data.
BST 675 covers the fundamentals of probability and inference through simulation. Topics are focused on methodology used in health data science and include, but are not limited to, random variables, independence, discrete and continuous distributions, confidence intervals, hypothesis testing, and efficient estimators.
BST 681, the first in a two-semester sequence in regression modeling, covers linear regression models for normally distributed outcomes. The course will cover simple and multiple linear regression, estimation, interpretation, hypothesis testing, model building and diagnostics, matrix algebra for regression, and an introduction to design of experiments. The course will include the use of computing tools to apply these models to real data.
BST 762 presents advanced statistical methods for analyzing longitudinal studies and repeated measures experiments. This course will cover methodology for linear mixed models, generalized linear mixed models and an introduction to nonlinear models as they apply to the analysis of correlated data.
This course aims to orient the student to the place health and health professions play in modern cultures. Recognition of their own social assumptions and values and those of persons of different backgrounds is encouraged. Understanding, predicting, and changing dental patient behavior from a social standpoint is emphasized.
Fundamentals of Dental Public Health is a first-year course designed to introduce student dentists to the dental specialty of Dental Public Health, to dental epidemiological concepts, terminology, and methods used in population-based health care. Community oral health problems in Kentucky and the United States will be reviewed. Emphasis will be placed on public health research, programming, and outcome evaluation strategies related to oral disease in populations.
