Health Statistics Concentration

Course #TitleCompetenciesCredits
Required
STAT 512/HDFS 590 Applied Regression Analysis (Fall, Spring, Summer) OR Linear Regression (Spring) 2,3,5/1,2,3,4,5 3/4
STAT 506 Statistical Programming and Data Management (Fall, Spring) 1,2 1
HK 590 Statistical Methods for Public Health Evaluation (Fall) 2,3,4,5 3
NUTR 590 Randomized Trials and Public Health (Spring) 1,2,3,4,5 3
Concentration Selectives (Choose 3 Credits)
ASM 540 Geographic Information Systems Aplication (Fall) 2,3,5 3
CE 597 Geospatial Modeling and Analysis (Even Fall - Pre-Req GIS Introduction) 2,3,5 3
CE 597 Geographic Information Systems (Spring) 2,3,5 3
CPB 619 Design, Conduct, and Analysis of Clinical Trials (Odd Fall) 1,3,4,5 2
CPB 625 Clinical Biostatistics (Spring) 1,4,5 2
CPB 626 Design and Analysis of Epidemiologic Studies (Odd Fall) 2,3,4,5 3
EDPS 607 Mixed Methods Research Designs and Application (Fall) 1,3,4,5 3
NUTR 590 Nutritional Epidemiology (Spring) 1,3,4,5 3
STAT 524 Applied Multivariate Analysis (Fall) (Pre-Req STAT 512) 2,3,4,5 3
STAT 522 Sampling and Survey Techniques (Spring) 3,4,4 3
STAT 582 Statistical Consulting and Collaboration (Spring - Pre-Req STAT 525) 1,3,4,5 3

Guidelines: For the health statistics concentration STAT 512/HDFS 590, STAT 506, NUTR 590, and HK 590 must be included on the plans of study. Plans of study must also include at least three credits additional credits from the list of concentration selectives or of an approved independent research/study project with a faculty mentor. Additionally, all health statistics competencies must be thoroughly covered.

STAT 506 — Statistical Programming and Data Management

Use of the SAS software system for managing statistical data. The SAS environment. Data description. Data access and management. SAS macro language and application development. 

STAT 512 — Applied Regression Analysis

Inference in simple and multiple linear regression, residual analysis, transformations, polynomial regression, model building with real data, nonlinear regression. One-way and two-way analysis of variance, multiple comparisons, fixed and random factors, analysis of covariance. 

STAT 522 — Sampling and Survey Techniques

Survey designs; simple random, stratified and systematic samples; systems of sampling; methods of estimation; costs.

STAT 524 — Applied Multivariate Analysis

Extension of univariate tests in normal populations to the multivariate case, equality of covariance matrices, multivariate analysis of variance, discriminant analysis and misclassification errors, canonical correlation, principal components, factor analysis. Strong emphasis will be placed on use of existing computer programs. 

STAT 582 — Statistical Consulting And Collaboration

This course is designed to emphasize and develop the skills needed by a statistical consultant/collaborator. Topics include: problem-solving, consulting session management, written and oral communication, research ethics, design of experiments, collection of data, and application of statistical methods to real problems. 

ASM 540 — Geographic Information Systems Application

Fundamentals of GIS analysis applied to environmental, agricultural and engineering-related problems. Topics include data sources; spatial analysis; projections; creating data and metadata; and solving spatial problems.

CE 597 — Geospatial Modeling and Analysis

The course intends to enhance students’ fundamental knowledge and advanced skills in geospatial science and technology. It will be focused on quantitatively exploring and evaluating the patterns of both physical and social phenomena in spatial and temporal domains. Students will learn the analytics needed for mining and interpreting geospatial data.

CE 597 — Geographic Information Systems

Introduces the principles, methods and skills in GIS. Enhance capabilities in handling and analyzing geographic data. Conduct GIS spatial analysis tasks. Design and create a geographic database. Experience internet mapping. Advance skills with ArcGIS and extensions. 

CPB 619 — Design, Conduct and Analysis of Clinical Trials

This course reviews the various types of clinical trials that are used in medical research, e.g., therapeutic and preventive. The stages and activities of a “typical” trial are defined along with factors that influence study design. Key elements of data collection, organization, analysis, and interpretation, and reporting of results are discussed and illustrated using published reports of clinical trials. Differences in the design and conduct of trials in humans and animals will be considered including the ethical concerns and costs. A graduate level introductory course in biostatistics is highly recommended prior to this course.

CPB 625 — Clinical Biostatics

Intended for professional medical and biological science graduate students, this course is designed to familiarize them with the appropriate usage (and reporting) of different statistical tests in biomedical research. Students will be taught the basic theories underlying the different tests, the data assumptions underlying the application of those tests, and will review/critique published scientific articles that employed these tests. Students will have the opportunity to describe the appropriate statistical methods to be used in their proposed research and/or report the usage of appropriate statistical tests on their own data. 

CPB 626 — Design and Analysis of Epidemiologic Studies

Focuses on epidemiologic study design and the applications of statistical software to the analysis of data derived from health research. Includes an overview of epidemiologic study designs, frequency and association measures, generalized linear models, and survival analysis.

HDFS 590 — Linear Regression

This course has two primary goals:

1) Provide students with foundational knowledge related to linear regression statistical analyses
2) Provide students with the opportunity to practice writing, interpreting, and presenting regression analyses for the purpose of dissemination

Two lectures per week will be focused on the key concepts and ideas of linear regression, and one lab session per week will be used to facilitate understading of SPSS as relevant to regression models. The objective of this course is to help students gain a familiarity and understanding of linear regression that will translate into their own research success. If done sucessfully, linear regression models can be the primary analysses that lead to publications, thesis defenses, and conference presentations. Additionally, more advanced statistical analyses often build on the foundational knowledge of linear regression. It is highly encouraged to attend all lectures and labs.

NUTR 590 - Randomized Trials and Public Health

By the end of this course, students will be able to: identify and plan an appropriate randomized study design to answer a substantive question; identify limitations to statistical evidence that arise in study design and implementation; analyze data from randomized trials using appropriate methods and good statistical practice; and interpret and communicate findings from randomized trials in an audience-appropriate way.

NUTR 590: Nutritional Epidemiology

The objective of this course is to familiarize students with nutritional epidemiology methods and research. The methods include study design, e.g. prospective cohort, case control and cross-sectional studies; nutrition surveillance and monitoring; and the validity and reliability of data collection tools such as dietary questionnaires, biomarkers of diet ant anthropometric measurements like weight and height for estimation of obesity

HK 590 - Public Health Program and Policy Evaluation

This course provides an overview of the methods required to evaluate the effectiveness of public health intervention or prevention program. The course introduces a range of quantitative, qualitative, and mixed methods research designs and the application and tailoring of these designs to evaluations. Issues associated with primary and secondary data collection, including sampling and survey design, are also covered. The course format is primarily “flipped.” You will learn about the material through online lectures and readings prior to classes.  Class time will be used to apply, analyze, and synthesize the material through activities, discussions, and guest presentations.

EDPS 607 - Mixed Methods Research Designs and Application

This course is intended to be an overview of mixed methods research designs within social science and educational research. The focus of the course will emphasize the philosophical pragmatism embedded in enacting mixed methods research. Further, the course will demonstrate the utility and plausibility of integrating quantitative and qualitative data into a single study. This demonstration will be accomplished through reviewing the historical context of qualitative and quantitative research in social sciences. Students will be primed for greater success in this course if they have background training and/or experience with quantitative AND qualitative methods. In addition to understanding the prominent mixed methods designs highlighted in the course readings, we will also pay attention to the inherent difficulties and barriers in conducting mixed methods research. Moreover, this class will allow you to focus on developing a research idea in which you implement or further your understanding of mixed methods. Lastly, this class will also call for you to attend to the usefulness of mixed methods research within your specific discipline (e.g., special education, counseling psychology, sociology, anthropology, etc.).

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