John D. Bower School of Population Health

Main Content

Courses of Instruction

CourseDescriptionHoursDelivery ModesInstructional Formats
BDS 706 - Ethics in Biostatistics and Data Science Research and PracticeThis interactive course encompasses traditional elements of responsible conduct of research training, best practices in data management and analysis, and ethical issues encountered during the development and application of biostatistical and data science methods. Topics covered include research misconduct, protection of human subjects, data management, reproducibility of research, authorship, collaboration, conflicts of interest and commitment, peer review, and healthy mentoring relationships, with accompanying case studies relevant to the data science field. Emerging issues in clinical trials, data science, and artificial intelligence will be discussed. Guidelines published by professional organizations composed of statisticians and data scientists will be reviewed. Class sessions will consist of a traditional lecture portion where concepts and definitions are explained, followed by one or more case study discussions1In-PersonLecture
BDS 790 - Doctoral Research Proposal IThe purpose of the course is to assist students through the proposal processes. This course covers the structure and content of a student dissertation research proposal, scientific writing conventions, strategies for conducting a literature search, critical evaluation and synthesis of literature, development of specific aims and research methods, procedures for writing and editing research proposals, and presentation of data.6In-PersonResearch
BDS 795 - Doctoral Research Proposal IIThe purpose of the course is to assist students through the proposal processes. This course covers the structure and content of a student dissertation research proposal, scientific writing conventions, strategies for conducting a literature search, critical evaluation and synthesis of literature, development of specific aims and research methods, procedures for writing and editing research proposals, and presentation of data. Students will also prepare their written research proposal.6In-PersonResearch
BDS 797 - Biostatistics & Data Science InternshipA work experience conducted in the Department of Data Science, an affiliated department, center, or institute at the University of Mississippi Medical Center, or a public or private organization. The internship is focused on the development of real world analytic, programming, and communication skills.1 - 9In-PersonInternship
BDS 711 - Statistical Methods in ResearchProvides an introduction to selected important topics in statistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data types and analysis techniques. Specific topics include applications of statistical techniques such as point and interval estimation, hypothesis testing (tests of significance), correlation and regression, relative risks and odds ratios, sample size/power calculations and study designs. While the course emphasizes interpretation and concepts, there are also formulae and computational elements such that upon completion, class participants have gained real world applied skills.3In-PersonLecture
BDS 712 - Statistical Methods in Research IIA continuation of Statistical Methods in Research 1, this course introduces the student to more complicated methods than those discussed in the first course including generalized linear models, survival models and longitudinal data analysis. The emphasis will be on applied rather than theoretical statistics, and on understanding and interpreting the results of statistical analyses. Datasets will be analyzed using the statistical package STATA. This is a hands-on class with computer labs. Datasets will be analyzed under the supervision of instructors.3In-PersonLecture
BDS 713 - Intro to Data Management and ProgrammingProvides an introduction to programming and data management. The course will focus on planning and organizing programs to handle and process data, as well as the grammar of particular programming languages.3In-PersonLecture
BDS 714 - Statistical Methods for Clinical TrialsProvides a basic understanding of the statistical concepts important in the design, conduct and analysis of clinical trials.3In-PersonLecture
BDS 715 - Intro to Sample Survey AnalysesProvides an introduction to statistical concepts in the design and analyses of sample surveys. Covers topics such as instrument design, sampling procedures, variance estimation, reliability, validity, scaling and scoring, complex samples and weighting procedures.3In-PersonLecture
BDS 721 - AnalyticsProvides an introduction to basic statistical and data analytic methods. This course covers topics such as data archetypes; exploratory data analysis; basic statistical paradigms including frequentist, likelihood and Bayesian approaches; contingency tables; sampling distributions; the Central Limit Theorem; point and interval estimation; sufficiency; tests of statistical significance including large sample, likelihood ratio and resampling approaches; basic random variable linear combinations; ANOVA; correlation; and linear, logistic, and Poisson regression. Course content will be delivered through lectures, hands-on lab instruction and team-based learning using multiple statistical packages (R, SAS and Stata).3In-Person

Online
Lecture
BDS 722 - Advanced AnalyticsContinues introductions to intermediate and advanced statistical analysis methods for biomedical research. This course covers advanced regression topics, generalized linear models (GLM), generalized additive models (GAM), splines and smoothing techniques, decision trees, basic survival models, and introduces machine learning techniques (clustering, classification, regularization/penalized regression, feature selection, Bayesian methods, and unbiased estimators). Course content will be delivered through lectures and hands-on lab instruction.3In-Person

Online
Lecture
BDS 723 - Statistical Programming with RThis course will provide students with an introduction to statistical computing. Students will learn the core ideas of programming functions, objects, data structures, flow control, input and output, debugging, logical design and abstraction through writing code to assist in numerical and graphical statistical analyses. This course will emphasize the learning of statistical methods and concepts through hands-on experience with real data. Since code is also an important form of communication among scientists, students will learn how to comment and organize code.3In-Person

Online
Lecture
BDS 724 - Longitudinal and Multilevel ModelsCovers statistical models for drawing scientific inferences from clustered\correlated data such as longitudinal and multilevel data. Topics include longitudinal study design; exploring clustered data; linear and generalized linear regression models for correlated data, including marginal, random effects, and transition models; and handling missing data.3In-PersonLecture
BDS 725 - Survival AnalysisThis course introduces basic concepts and methods for analyzing survival time data obtained from following individuals until occurrence of an event or their loss to follow-up. We will begin this course from describing the characteristics of survival (time to event) data and building the link between distribution, survival, and hazard functions. After that, we will cover non-parametric, semi-parametric, and parametric models and two-sample test techniques. In addition, we will also demonstrate mathematical and graphical methods for evaluating goodness of fit and introduce the concept of dependent censoring/competing risk. During the class, students will also learn how to use SAS to analyze survival data.3In-PersonLecture
BDS 726 - Generalized Linear ModelsProvides a foundation in the theory and application of generalized linear models and related statistical topics. A generalized linear model (GLM) is characterized by (1) a response variable with a distribution in an exponential dispersion family and (2) a mean response related to linear combinations of covariates through a link function. GLMs allow a unified theory for many of the models used in statistical practice, including normal theory regression and ANOVA models, many categorical data models including logit and probit models for binary data, loglinear models, and models for gamma responses and survival data.3In-PersonLecture
BDS 727 - Nonparametric AnalysesProvides an introduction to modern topics in nonparametric data analysis for estimation and inference. Topics include kernel estimation, rank based methods, nonparametric regression, confidence sets and random processes. Methodology and theory are presented together.3In-PersonLecture
BDS 728 - Multivariate AnalysisProvides an introduction of the analysis of multivariate data, balancing theory, implementation and translation of these methods. Topics covered include  matrix computations, visualization techniques, the multivariate normal distribution, MANOVA, principal components analysis, factor analysis, and other  clustering techniques.3In-PersonLecture
BDS 739 - Computational StatisticsThis course will cover efficient methods for obtaining numerical solutions to statistical problems. Topics include numerical optimization in statistical inference [expectation-maximization (EM) algorithm, Fisher scoring, etc.], Monte Carlo methods, random number generation, jackknife methods, bootstrap methods, kernel density estimation, and splines.3In-Person

Online
Lecture
BDS 741 - Statistical Inference IIntroduces probability and distribution theory, including axioms of probability; random variables; probability mass and density functions; common discrete and continuous distributions; transformations and sums of random variables; expectations, variances, and moments; hierarchical models and mixture distributions; and properties of random samples.3In-Person

Online
Lecture
BDS 742 - Statistical Inference IIThis course is a continuation of Statistical Inference I and continues to introduce modern statistical theory and principles of inference based on decision theory and likelihood (evidence) theory.3In-PersonLecture
BDS 743 - Theory of Linear ModelsProvides an introduction to the development and use of general linear models including frameworks for parameter estimation and inference in a variety of settings. Theoretical foundations of the models will be reinforced with areas in which the models are applied to answer scientific questions. Topics covered include matrix algebra, distribution theory for quadratic forms of normal random vectors, properties of OLS estimators, estimable functions and related themes.3In-PersonLecture
BDS 750 - Study Design in Clinical TrialsThis course will equip doctoral-level biostatisticians and data scientists with the skills necessary to participate in the design, planning, and analysis of biomedical, clinical, and population-based health studies. This course will cover a wide array of experimental and observational study designs with corresponding analytic methods.  Many aspects of clinical trial design and analysis will be covered in detail. A consistent and unifying process to develop the optimal study design feasible in collaboration with subject domain expert investigators will be emphasized.  The course also serves as a transition where the student's accumulated foundational theory and methods knowledge is translated and applied to typical biomedical investigative questions.3In-Person

Online
Lecture
BDS 751 - Statistical Inference in GeneticsThis course will present fundamental theoretical concepts and statistical inference with emphasis on genetic epidemiology research for common human diseases. Five modules will be covered, including an introduction to statistical inference methods used on genetic data, familial aggregation methods, segregation analysis, linkage analysis, and testing associations between genetic variants and disease.3In-PersonLecture
BDS 752 - Advanced Statistical GeneticsAn advanced course on modeling and methodology in statistical genetics for human diseases and traits. The course will cover topics including linkage analysis, population structure and stratification, admixture mapping, heritability and genetic risk prediction, familial aggregation, association analysis and others. On successful completion, participants will have the skills to develop and apply statistical methods towards a variety of genetic questions.3In-PersonLecture
BDS 753 - BioinformaticsProvides an introduction to selected important topics in bioinformatics. The course focuses on integrating bioinformatics resources with basic biology and clinical applications to enhance population health research.  Includes methods for the analysis of high-throughput next-generation sequence data and an introduction to the use of bioinformatics databases in precision medicine and population health. Covers common programs and algorithms for sequence alignment, evolutionary tree construction, database searching, functional interpretation of expressed genes, and identifying genetic mutations for human disease.3In-PersonLecture
BDS 754 - Principles of Programming with PythonThis course will introduce fundamental programming concepts such as data structures and algorithms, object oriented programming, and the basics of building interactive applications in the python programming language.3In-Person

Online
Lecture
BDS 761 - Data Science and Machine Learning IProvides a modern introduction to data science, including data wrangling and dynamic data visualization processes, while reinforcing reproducible research and applied machine learning methods. Course content will be delivered through lectures and hands-on lab instruction.3In-PersonLecture
BDS 762 - Advanced Data ScienceProvides a continuation into advanced Data Science topics with deeper programming and additional concepts. Topics include simulation, bootstrap, prediction, machine learning, and tool development. Course content will be delivered through lectures and hands-on lab instruction.3In-PersonLecture
BDS 763 - Database SystemsReview of database systems with special emphasis on data description and manipulation languages; data normalization; functional dependencies; database design; data integrity and security; distributed data processing; design and implementation of a comprehensive project.3In-PersonLecture
BDS 764 - Data VisualizationProvides an introduction to principles and techniques for creating effective interactive visualizations of quantitative information. Primary topics include principles for designing effective visualizations and implementing interactive visualizations using web-based frameworks.3In-PersonLecture
BDS 765 - Data Science and Machine Learning 2This course introduces students to the basic theories, concepts, and techniques of machine learning and gives them a glimpse of the state-of-the-art methods in this area. Topics covered include Bayesian estimation and decision theory, maximum likelihood estimation, nonparametric techniques, linear discriminant analysis, computational learning theory, support vector machines and kernel methods, boosting, clustering, dimensional reduction, and deep learning.3In-PersonLecture
BDS 766 - Advanced Computational MethodsProvides a blend of software engineering, stochastic processes and optimization for creating and deploying efficient analytic tools. Topics covered include software engineering paradigms, robust software design, data structure, object oriented design, parallel computations, and distributed computing, with a focus on implementation.3In-PersonLecture
BDS 767 - Deep Learning ApplicationsThis course will review the basic concepts of deep learning convolutional neural networks (CNNs), emphasizing application development. Students will be exposed to decent technologies and open-source tools such as PyTorch, TensorFlow, Keras, Jupyter Notebook, and Jetson Nano. Students will be able to design a deep learning project and complete all processes from data collection, model training, and model deployment upon completing hands-on labs and projects. It is anticipated that this course will help students enhance their thesis/dissertation research and participate in funded projects.3In-Person

Online
Combination
BDS 791 - Special TopicsThis course is intended to meet special needs of individual students. Students who wish to learn more about a particular topic can approach a mentor to determine an advanced course of study for that topic. The structure of an individual course is decided upon by the course director with approval from the curriculum committee.1 - 9In-PersonIndependent Study
BDS 792 - Statistical ConsultingProvides hands-on training and experience in statistical consulting. Written and oral communication skills are emphasized, working with collaborators/investigators on new and ongoing research projects.  Developing a consistent process and approach to statistical consultation & collaboration is emphasized. Commonly encountered statistical consulting questions/issues such as endpoint formulation, multiple comparisons, and sample size are addressed. Along with BDS 750, Study Design, this course emphasizes the transition from theoretical and methodological knowledge accumulation to real-world application in biomedical research.3In-PersonInternship
BDS 793 - Seminar Series: MicrotopicsThis course consists of attending the weekly Department of Data Science faculty seminar series. The goal of this seminar course is to expose students to current research topics in the field, to also give them exposure to seminar presentations, and to offer further detail into faculty research areas to assist in proposing a dissertation topic and research mentor.1In-PersonLecture
BDS 794 - Journal ClubThis biweekly journal club will include student presentations of high-impact or seminal biostatistics, data science, or genomics journal articles. Each participating student will be required to present once per semester, with additional presentations by non-registered students, faculty, and staff.1In-PersonLecture
BDS 796 - Directed ResearchProvides students to the opportunity to conduct research under the guidance of a faculty member from the Department of Data Science.3In-PersonLaboratory
BDS 798 - Dissertation ResearchResearch and preparation of a dissertation.1 - 9In-PersonThesis
PHS 700 - Essentials of Population HealthIntroduction to how the multiple determinants of health (e.g., health care, socioeconomic status, genetics, the physical environment and health behavior, and their interactions) have implications for the health outcomes of populations.  Characteristics of populations defined by geography, diagnosis, and/or point of care will be discussed. Avenues in which health care systems, public health agencies, community-based organizations, retail health organizations work together to improve local, national, and global communities.  Students will also learn how to view problems from a population health and population health management perspective. Descriptions of how clinical and non-clinical data is used to measure health-related outcomes, analyze patterns, communicate results, and develop evidence-based intervention practices to manage of health of populations will be explored.3In-Person

Online
Lecture
PHS 701 - Applied DemographyThe course provides an applied overview of common methodological approaches, major conceptual issues, and recent empirical research in demography. Demography is the study of the causes and consequences of population change. Populations change in size and composition in response to three basic phenomenon: fertility, mortality, and migration. Course readings and discussions will draw on research in multiple disciplines to provide students a framework for evaluating how social, economic, historical, cultural, and political factors interrelate with these demographic processes. Students will be introduced to the data, statistics, and substantive issues of demography including mortality, fertility, migration, population composition, population distribution, population policy and the relationship between population and environment.3In-Person

Online
Lecture
PHS 702 - Statistical Methods in ResearchThis course provides an introduction to selected important topics in statistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data types and analysis techniques. Specific topics include applications of statistical techniques such as point and interval estimation, hypothesis testing (tests of significance), correlation and regression, relative risks and odds ratios, sample size/power calculations and study designs. While the course emphasizes interpretation and concepts, there are also formulae and computational elements such that upon completion, class participants have gained real world applied skills.3In-Person

Online
Lecture
PHS 703 - Epidemiology IThis course will introduce students to the principles and methods of epidemiology in human populations, including study design (randomized trials, case-control studies, cohort studies, and cross-sectional studies), risk estimation, and methods of causal inference.3In-Person

Online
Lecture
PHS 704 - Epidemiology IIThis course will present and illustrate advanced concepts in epidemiologic methods with an emphasis on observational studies. Topics include causal inference in epidemiology, measures of disease frequency, measures of association, application of statistical methods commonly used in epidemiologic studies (e.g., stratified and logistic regression analysis), calculation of sample size and statistical power, precision and validity in epidemiologic studies, quantification of bias (e.g., information and selection bias), assessing confounding and effect modification, interpretation and critique of results from various epidemiologic studies including meta-analysis3In-Person

Online
Lecture
PHS 705 - Value-based Healthcare Del & Pay ModelsHealth care systems in the US and around the world are pursuing value-based health care (VBHC) reforms that seek to achieve the Triple Aim, now the Quadruple Aim of better care for individuals, better health for populations, lower cost of care per capita and improving the clinician experience. In VBHC, health care payers and purchasers hold health care providers accountable for delivering high-quality care and spending health care dollars more wisely. VBHC delivery models include Accountable Care Organizations (ACOs), Integrated Delivery Networks (IDNs), Clinically Integrated Networks (CINs) and other models. These systems which can be composed of hospitals, doctors, and other health care providers or subsets of these, share financial and clinical responsibility for providing coordinated care to patient populations in hopes of limiting unnecessary spending and improving outcomes. Payment models will be covered from quality-based fee-for-service to global capitation.3In-Person

Online
Lecture
PHS 707 - Accountable Care OrganizationsAccountable Care Organizations (ACO) are designed to provide high quality health care and control costs; two components of the Quadruple Aim.  The focus of this course will be to examine different types of ACOs and their various payment characteristics, organizational structures, mixed capabilities, governance structures, and varied contracts, and to explore the interventions conducted within ACOs at both the organizational and patient-levels.3OnlineLecture
PHS 709 - Population Health ManagementThis course will introduce students to the applied field of population health management through the use of case studies and key elements of population health management such as development of accountable care processes and infrastructure, payer relationships, care coordination, health and financial management systems, and leadership.  Descriptions of how clinical and non-clinical evidence is used to measure health-related outcomes, analyze patterns, communicate results and identify best practices and implement effective interventions to manage the health of clinical populations.  The importance and challenges of the translation of data and information into intelligence for clinical and health policy decision-making will be emphasized.3In-Person

Online
Lecture
PHS 710 - Lifestyle Medicine and Health CoachingThe purpose of this course is to increase the knowledge and skills of clinicians in coaching patients to make lasting lifestyle management changes utilizing evidence-based lifestyle medicine strategies. It is envisaged that undertaking this subject will contribute to the professional development, knowledge base and performance of those involved in health promotion and chronic disease management. Given the evolution of the U.S. health care system, health care providers are incentivized to produce better patient outcomes and to reduce recurring patient visits. Employers are prioritizing health and wellness in the workplace, aiming to cut costs and increase productivity. Given these changes, it is important for clinicians to increase their skill set in the provision of lifestyle modifications , as well as enhancing their knowledge of evidence-based approaches for motivating behavior change, and understanding of how to incorporate lifestyle medicine into clinical practice3OnlineLecture
PHS 711 - Healthcare Quality and SafetyThis course provides an overview of health care quality and safety. Students will learn fundamental quality improvement concepts and techniques. Quality measurement, assessment, and improvement frameworks will be explored as they apply to clinical, safety, and patient satisfaction outcomes.3In-Person

Online
Lecture
PHS 712 - Science Communication & Dissemination IThis is a foundation course in science communication theory, research, and practice in the context of health promotion and health care. This course is based on the premise that scientists, and increasingly, other practitioners and educators, are agents of change in creating research impact, promoting research utilization, and ensuring that research findings reach appropriate audiences. This course is designed to increase practical knowledge, competencies and skill set necessary for translating scientific knowledge to various communities and populations.3In-Person

Online
Lecture
PHS 713 - Implementation ScienceThis course is an introduction to implementation science and its relevance to population health science and practice. Implementation science is the scientific study of methods to promote the uptake of research findings in real world settings such as clinical, organizational, community, or policy environments. The course will first highlight current challenges in population health and the role of implementation science in addressing them, including the development of practice-based research activities and the provision of technical support for program implementation. Common implementation research frameworks will be introduced.3In-Person

Online
Lecture
PHS 714 - US Healthcare Organizations and DeliveryFocuses on the organization, financing, and delivery of healthcare in the U.S. Contrasts the private and public sectors and examines the effects of market competition and government regulation. Examines the ways that medical providers are paid, and explores the major issues currently facing physicians, hospitals, and the pharmaceutical industry. Also discusses several potential small and large scale reforms to the U.S. healthcare system and evaluates their likely effects on healthcare spending, quality of care, and access to care.3In-Person

Online
Lecture
PHS 715 - Health Disparities SeminarThis course will examine relevant historical issues, theories, and empirical data, emphasizing critical analysis and application of knowledge. Disparities will be discussed relative to race/ethnicity, gender, income, and sexual orientation. Students will gain a better understanding of research on health disparities and interventions to promote health equity through a combination of readings, reflection papers, and in-class exercises. Students will summarize the evidence regarding a specific health disparity (topic and population of their choice).3In-Person

Online
Lecture
PHS 716 - Interventions for Org. Behavior ChangeThis course is designed to provide students with a conceptual framework addressing the strategic importance of managing change and organization development (OD) in various agencies, health care organizations, human service organizations, community organizations and other settings. Uncertainty, complexity and rapidly changing organizational environments create the necessity for organizations to respond to and effectively deal with turbulence and instability. The capability of an organization's human resources to adapt to such conditions, adopt and successfully use new practices, technologies and develop ways of performing organizational tasks is vital to proactive and sustainable human service organizations. Managing change and OD are essential to these processes. Students will also learn LEAN and six sigma methodologies as key tools for process improvement in healthcare settings that require the management of multidisciplinary teams.3In-Person

Online
Lecture
PHS 717 - Health Behavior TheoryThis course will provide an overview of social and behavioral science theories and frameworks that are currently used to: 1) understand health related behaviors; and 2) guide development of interventions and policies designed to prevent, reduce or eliminate major public health problems. Population health is an interdisciplinary field built upon other disciplines such as sociology, psychology, economics, demography, and public health. As a result, this course will cover classic theories in psychology and sociology; the leading health behavior theories in public health, and emerging theories used in population health interventions.3In-Person

Online
Lecture
PHS 718 - ProseminarProseminars are professionalism courses that provide entrance into a field. This course will review the evolution of the field of population health science, the school of population health, and future developments in this field. Learners will also engage with population health professionals employed in a variety of settings, spanning the scope of the profession of population health.3In-PersonLecture
PHS 720 - Population Health InformaticsThis course will focus on the concepts, theories and practices of the evolving discipline of health informatics.  Differentiation between approaches used in this field versus health information technology will be highlighted.  Health informatics is defined as the method of acquiring, storing, retrieving, and using healthcare information to foster better collaboration among patients and health care providers. This evolving specialization links information technology, communication and health care to improve the quality and safety of patient care.3In-Person

Online
Lecture
PHS 721 - Digital HealthcareThis course introduces students to the utility of information and communication technologies (ICT) within modern healthcare practice. Students will learn about a range of digital technologies and applications in the areas of clinical practice, education and administration that are fast becoming commonplace. The course fosters awareness of digital health at national and international levels; it examines the characteristics of digital health innovation, strategic vision and deployment in various countries such as Australia, US, Canada, Europe and the developing world. While evaluating the technological advances relative to patient-centered care, students will also study the potential pitfalls of the use of technology in healthcare. The course draws attention to the associated social, ethical, legal issues and workflow issues that must be considered when integrating digital health into clinical practice.3In-Person

Online
Lecture
PHS 722 - Health Information VisualizationInformation visualization is the use of interactive visual representations of data to amplify human cognition. This course provides an introduction to the theories, principles and techniques for creating effective interactive visualizations of quantitative health information.  The course will take a hands-on approach and will teach how to carry out visual analytics using a modern data visualization software.3In-Person

Online
Lecture
PHS 724 - Environmental HealthThis course offers a general introduction to environmental health from global to local, addressing fundamental topics and current issues. This course covers core topics that prepare students to comprehend environmental health issues leading to prevention and management of the major environmental health problems.3In-PersonLecture
PHS 730 - Health Prom, Disease Prev, and Care MgtThe course is concerned with the socio-cultural, behavioral, psychological, and biological factors contributing to wellness and disease prevention. Students will be introduced to the theory and application of health promotion principles and will review and critically assess the current efforts to influence lifestyle change, at both the individual and population levels.3In-Person

Online
Lecture
PHS 731 - Social Determinants of HealthThis course analyzes the social factors, such as inequalities in income and opportunities, and racial/ethnic disparities that influence the health of populations. The course examines the effect of economic, social, cultural, and environmental factors on population health. The course looks at how systematic variation in these factors lead to health disparities, and explores how economic, social and cultural conditions interact with other determinants of health such as human behavior and biology. The course also reviews the methods used in health disparities research and assesses relevant economic and social policies.3In-Person

Online
Lecture
PHS 732 - Global Health: Disp, Deter, Pol, & OutThis course will focus on four main topics: 1) the burden and distribution of disease and mortality; 2) the determinants of global health disparities; 3) the development of global health policies; and 4) the outcomes of global health interventions. Substantial attention will be given to the difference in terminology used to describe inequalities across countries, the underlying historical assumptions that undergird those definitions, and the resulting solutions that are implemented as a result. Factors that highlight how global health disparities and global health policy responses are shaped by social, economic, governmental, and political forces will be discussed.3In-Person

Online
Lecture
PHS 739 - Science Communication & Dissemination IIThis is an applied course in science communication and dissemination, designed to advance students? knowledge of health and science communication theory, research, and practice. The major course objective is to provide opportunities to develop skills in communicating complex scientific information and study findings to multiple audiences. The course will expose students to various contexts for science communication including interpersonal, small group, and mass media.3In-Person

Online
Lecture
PHS 740 - Foundations of Scientific WritingThis course covers how to write a research grant proposal. This will include how to write the main components of the research strategy with appropriate specific aims. Grant submission, review, and award cycles will also be presented.   This course will provide students with fundamental skills for writing scientific grants.3In-Person

Online
Lecture
PHS 742 - Multivariate RegressionThis course introduces the basic concepts and steps associated with multivariable statistical modeling. It integrates methods with performing the steps using data analysis tools such as Stata. Presents use of generalized linear models for quantitative analysis of data encountered in public health and medicine. Specific models include analysis of variance, analysis of covariance, multiple linear regression, logistic regression, and Cox regression. Applied linear regression involving hands-on data analysis will be emphasized. Students enrolling for this course should have taken at least one other graduate level statistics course and should be conversant with the basic fundamentals of statistical testing and estimation.3In-Person

Online
Lecture
PHS 743 - Prgm Eval for Pop-Level InterventionsThis course is designed to cover a wide range of assessments including individual programs, institutional and governmental policies. Evaluators work with program staff and stakeholders to clarify a program's operational theory and goals, develop information to help tailor an intervention to a specific audience, document a program's specific activities, reach, and outcomes, and develop information about the impact of a program or policy on a specific community health concern. This practical course will cover the core knowledge and skills involved in program evaluation, provide hands-on experience in evaluation design, and provide exposure to some of the ethical and philosophical issues current in evaluation research. The course will be conducted entirely online. Course activities will be focused on giving students hands-on experience in the specific research skills and tools required for effective program evaluation.3In-Person

Online
Lecture
PHS 744 - Bioethics and SocietyThis is a case-method course, consisting of discussion of the fundamental basics of bioethical theory. In this class, students will learn the fundamentals of bioethical theory and then apply this knowledge in developing a language and toolbox for making decisions when faced with dilemmas and ethical conflicts in a healthcare setting and in regard to issues of health and healthcare. The underlying concepts are vital to selecting and applying the appropriate frame to view these dilemmas and ethical conflicts.1 - 2In-Person

Online
Lecture
PHS 745 - Comm Eng and Comm-Based Particip RsrchCommunity engagement strategies that affect health behavior are increasingly important for improving the health of populations. Introduces the principles and applied methods of community-engaged research, including defining the community and partnership models for identifying relevant research questions. The course will cover community assessment, coalition building, choosing community partners, ethical issues of community work and important methodological issues of community-based participatory research. It is intended to develop and expand the skills of population health professionals in designing and delivering culturally congruent health promotion program in community settings.3In-Person

Online
Lecture
PHS 746 - Systematic ReviewThis course introduces the methods of systematic review and meta-analysis, including formulating questions, criteria for relevance and rigor in selecting primary studies, search strategies, coding protocols, tables and other formats for presenting data, qualitative and quantitative representations of effect sizes from individual primary studies, and analyses of groups of studies to estimate an average effect size and to explain variation. Each student works on his/her own project with the goal of producing a complete proposal/protocol and taking preliminary steps in all phases of the systematic review process. This course will include A STATA-based workshop in meta-analysis. The course will also provide an overview of evidence-based medicine and evidence-based public health practice.3In-Person

Online
Lecture
PHS 747 - Qualitative Methods and AnalysisThis course will use a combination of didactic, interactive, and applied techniques to teach methodological and analysis techniques in survey research. Students will review theoretical approaches and explore the connections between overarching theoretical frameworks, data collection methods, and analysis strategies. Students will have the opportunity to learn and practice survey development and implementation methodologies and will practice coding techniques for data analysis.3In-PersonLecture
PHS 748 - Spatial Analysis and GISIntroduces the field of spatial analysis and its application to population health research and planning. Concepts are examined through the use of ArcGIS Geographic Information System (GIS) mapping software as a tool for integrating, manipulating, and displaying health related spatial data. GIS topics covered include mapping, geocoding, and manipulations related to data structures and topology. Introduces the spatial science paradigm: Spatial Data, GIS, and Spatial Statistics. Selected case studies are used to demonstrate concepts along the paradigm. Focus is on using GIS to generate and refine hypotheses about population health related spatial data in preparation for follow up analyses. Prerequisite: PHS 702 Statistical Methods in Research or equivalent.3In-Person

Online
Lecture
PHS 749 - Longitudinal and Multilevel ModelsThis course offers an in-depth exploration of advanced statistical techniques essential for population health research. Designed to build upon foundational statistical knowledge, the course provides exposure to a range of topics, which may include generalized linear models (GLM), multilevel modeling, longitudinal data analysis, survival analysis, structural equation modeling, and the application of sampling weights in complex survey designs. Emphasizing both theoretical understanding and practical application, students will engage in hands-on analysis of health data, learning to interpret and apply advanced statistical methods in real-world population health research contexts.3In-PersonLecture
PHS 750 - Population Health Research Methods IThis course will introduce the major components in research methods including: qualitative and quantitative study designs, selection of study populations, formulation of research questions, hypothesis formulation, levels of measurement, sampling, measurement, instrumentation, and study interpretation issues. Emphasis will be placed on research methods from social science origins, including an introduction to qualitative research theory and design.3In-Person

Online
Lecture
PHS 752 - Designing and Conducting Health SurveysThis course is a theoretical and practical overview of survey methodology, with survey research design and implementation as the major focus. Central to this course is survey quality, the variety of settings in which survey data is collected, devices for data collection, data processing, and survey data analysis techniques. Best practices and guidelines for phases of survey from design to implementation, analysis and reporting will be discussed.3In-Person

Online
Lecture
PHS 753 - Systems Science and Population HealthThis course provides an introduction to systems science and its applications to population health science and practice. Health and health care improvement challenges tend to be complex and involve multiple actors and institutions. Unlike traditional cause and effect or linear thinking models, systems thinking and complexity science is characterized by nonlinearity, hence traditional statistical methods are often inadequate for analyzing or predicting outcomes that depend on many interacting and adaptive parts. Systems thinking is a core skill that helps health professionals build programs and policies that anticipate and prepare for unintended consequences. Students will learn new ways of thinking about problem solving, including a range of powerful conceptual techniques suitable for planning interventions in complex and uncertain environments and use of systems models to devise strategies to account for real world complexities in research translation.3In-Person

Online
Lecture
PHS 755 - Improving the Health of Vulnerable PopThe course provides intensive coverage of contemporary topics in vulnerable populations in health care and health research. It explores definitions of vulnerability and provides a conceptual model for considering issues of vulnerability in a health care, health research, or public health context. It guides students through practical considerations for working with a variety of vulnerable populations.3In-Person

Online
Lecture
PHS 756 - HIV/AIDS in the United StatesThis course offers an immersion experience in the HIV/AIDS epidemic in the United States. Seminar topics to be covered include: historical context, epidemiology and trends, wide and persisting disparities, old and emerging challenges, and advances and opportunities in prevention and treatment. Students will have an immersion experience in nationally acclaimed cutting-edge research and service programs in Jackson, Mississippi, with emphasis on improving equity for sexual minorities with or at-risk for HIV infection.3In-Person

Online
Lecture
PHS 757 - Health Equity Reserch MethodsThis course covers theory and practical methods for developing and conducting research with the goal of improving health equity. Introduces methods and skills required to conduct rigorous health equity research and translate evidence-based strategies into practice and policy. It goes beyond methods for identifying health disparities to methods for addressing such disparities through research.3In-Person

Online
Lecture
PHS 760 - Health EconomicsThis course covers the theory of microeconomic analysis and its application to health and health services. It emphasizes the use of theory to understand problems of organization, delivery, and financing of health services; discrepancies in health levels among members of society; and the choices available to society regarding these issues. Doctoral students will be required to write a paper that identifies and discusses the major policy and research issues in one of the areas of health economics that is introduced in the course.3In-Person

Online
Lecture
PHS 761 - Healthcare FinanceThis course covers key financial concepts and principles in the health care industry. Managerial and financial accounting, as well as financial analysis and strategic planning, are covered. Financial management under prospective payment and capitation systems, as well as product costing and pricing, will be emphasized. Risk-based contracting and other anticipated changes to financial management due to health care reform will be introduced.3In-Person

Online
Lecture
PHS 762 - Methods for Econ Eval of Health ProgramsThis course deals with comparative effectiveness research that takes cost into consideration. It covers the concepts and methods for the economic analysis of healthcare decision alternatives. Topics will include cost-benefit, cost-effectiveness and cost-utility analysis, and other methods of decision analysis. It emphasizes the application of these methods to the evaluation of alternative health programs. Prerequisite: PHS 760 Health Economics.3In-Person

Online
Lecture
PHS 763 - Econometrics for Population HealthThis course provides an introduction to estimation, testing, and interpretation of linear and non-linear econometric models; helps students develop the quantitative skills necessary for using these techniques; and provides experience in using software for econometric analysis. Students will critically evaluate health and healthcare studies conducted with econometric methods. Topics covered includes multi-collinearity; auto-correlation and heteroscedasticity; specification tests; random and fixed effect models; endogeneity and instrumental variables; simultaneous equation models; and selection models.3In-Person

Online
Combination
PHS 764 - Applied MicroeconometricsThis course provides in-depth coverage of modern microeconometric methods to enhance problem solving skills and improve students’ confidence in selecting techniques properly suited to the data and to the economic model. The limitations and pitfalls associated with each microeconometric technique will be discussed. The lectures and workshops will provide both mathematical rigor and the opportunity to gain practical experience with relevant software applied to empirical datasets3In-Person

Online
Combination
PHS 765 - Advanced MicroeconomicsThis course covers advanced topics in microeconomic theory and shows how the principles of microeconomic theory explains general characteristics of economic behavior in the health sector. Topics will include the applications of microeconomic analysis to questions dealing with the production and supply of health services, demand for health services, market equilibrium, health insurance, and government regulation activities in the health sector. It provides sufficient training in the methods of microeconomics to enable students conduct independent research by themselves3In-Person

Online
Lecture
PHS 766 - Behav., Econ., & Health Decision-MakingBehavioral economics is the study of emotional and psychological influences on decision making. This course offers an introduction to behavioral economics and its applications to health and health care decision-making. It covers theories behind why people make certain health-related economic decisions, especially when those decisions may be contrary to their best interest. Students will learn the impact that behavioral factors affecting patients, providers, and patient-provider interaction can have on decision-making, treatment choices, costs, and health outcomes. Application of behavioral economics to influencing patient and provider behavior in health care settings, as well as application of behavioral economics to public policy making will be covered.3In-Person

Online
Lecture
PHS 790 - Special topics in PHSThe focus of this Special Topics course may vary by semester. It is designed to respond to contemporary issues in population health as well as to cover specific areas of faculty and/or students interest.1 - 3In-Person

Online
Lecture
PHS 791 - Independent StudyThis course is intended to meet special needs of individual students. Students who wish to learn more about a particular topic can approach a mentor to determine an advanced course of study for a particular topic. The structure of an individual course is decided upon by the individual course instructor with approval from the program committee.1 - 9In-Person

Online
Independent Study
PHS 796 - Directed ResearchThe purpose of this culminating course is for students to produce a written, independent scientific research work. During the course, students will demonstrate their ability to independently plan, carry out and present (orally and written) their research on a topic that addresses a current population health-related issue. This involves formulating a research question and objectives, selecting appropriate methods, collecting and analyzing data, and presenting and discussing results in relation to relevant scientific literature.1 - 9In-Person

Online
Research
PHS 797 - Population Health CapstoneThis capstone course will offer students the opportunity to apply knowledge and skills acquired in their prior course work in the program. It is designed as a final project through which students will gain a culminating and integrative experience in the application of population health science and management concepts. The project could take many forms, such as a proposal or pilot of an intervention to improve one or more dimensions of the Quadruple Aim in a specified setting, a consulting project for a real-world organization, a simulation activity, or an evaluation. Business and academic written and oral communication skills will be demonstrated.1 - 6In-Person

Online
Internship
PHS 798 - Doctoral Dissertation ResearchThis is seminar course for doctoral students in Population Health Science who are currently working on their dissertation. The seminar provides students the opportunity to present and discuss their work in a supportive environment. Faculty may also present ongoing research.1 - 9In-Person

Online
Thesis
PHS 799 - Doctoral Proposal DevelopmentThis course deals with both the theoretical and practical aspects of designing dissertation research and successfully defending the design in a proposal hearing. The purpose of the course is to assist students through the proposal and dissertation writing processes. This course covers the structure and content of a student dissertation research proposal, scientific writing conventions, strategies for conducting a literature search, critical evaluation and synthesis of literature, development of specific aims and research methods, procedures for writing and editing research proposals, and presentation of population health information. Students will be introduced to the process of acquiring and managing extramural funding for sponsored projects with emphasis on NIH research grants. Students will be encouraged to flesh out their doctoral dissertation proposal and to complete a pre-doctoral grant application during this course.6In-PersonResearch
PM 797 - Preventive Medicine PracticumThis course provides an opportunity for students to apply their knowledge of core topics in clinical prevention and population health in the health care environment, and to communicate about these topics with other physicians.1 - 9In-Person

Online
Internship
PHS 725 - GIS in Healthcare and EpidemiologyThis course prepares students to apply geographic information systems in population health related studies. This course combines the understanding of spatial analysis and application. This is the second level graduate GIS at UMMC.3In-Person

Online
Lecture
PHS 726 - Intro to GISThis course introduces the fundamental concepts and applications of geographic information systems. Special emphasis is given in the areas of healthcare and epidemiology. This course combines an overview of the general principles of GIS and analytical use of spatial information technology applicable for health professionals. This is the first course of a series of geospatial information technology at UMMC.3 - 4In-Person

Online
Lecture
PM 725 - Environmental HealthThis course offers a general introduction to environmental health from global to local, addressing fundamental topics and current issues. This course covers core topics that prepare students to comprehend environmental health issues leading to prevention and management of the major environmental health problems.3In-Person

Online
Lecture