PUBH 6541 01F - Biostatistics (Online)

This course examines statistics in public health and related sciences, including sampling, probability, basic discrete and continuous distributions, descriptive statistics, hypothesis testing, confidence intervals, categorical data analysis, regression, and correlation. Emphasis will be on the development of critical thinking skills and health data analysis applications with computer software

PUBH 6541 - Categorical Data Analysis

(taken from 2012-13 Course Catalog): This course introduces statistical methods for analyzing both univariate and multivariate categorical data and count in medical research and other health-related fields. The course will introduce how to distinguish among the different measurement scales, the commonly used statistical probability distribution and inference methods for categorical and count data. Emphasis will be placed on the application of the methodology and computational aspects rather than theory. The students will learn how to apply SAS procedures to data and interpret the results

BIOS 9433 - Analysis with Missing & Miss-specified Data

This course is designed to provide the student with the basics of methods for analyzing data with missing data and misspecified data. This course will cover the following topics: missing data in experiments, complete case analysis, weighted complete case analysis, available case analysis, single imputation methods such as mean, regression, last value varied forward, hot deck imputation, cold deck imputation, Bayes Imputation, Multiple imputation, and non-ignorable missing data models. Prerequisite: A minimum grade of “B” in BIOS 9131. Co-requisite: BIOS 9231

PUBH 7140 – Applied Statistical Methods in Public Health

This course will provide broad overview of statistical methods and commonly used software to analyze the public health data, emphasizing interpretations and concepts. It will focus on developing the ability to read the scientific literature to critically evaluate study designs and methods for secondary data analysis. It also will introduce students about the commonly used statistical software package SPSS to manipulate data and prepare them for remaining course work for their concentration. Students will use statistical software (SPSS) to analyze data originating from various survey designs, including data from experimental designs. Emphasis will be placed on the development of critical thinking skills, statistical reasoning, and collaboration. Students will learn to apply the concepts covered in class through a semester-long hands-on analysis of real public health data using statistical software

BIOS 6531 – Categorical Data Analysis

(taken from 2017-18 Course Catalog): This course introduces statistical methods for analyzing both univariate and multivariate categorical data and count in medical research and other health-related fields. The course will introduce how to distinguish among the different measurement scales, the commonly used statistical probability distribution and inference methods for categorical and count data. Emphasis will be placed on the application of the methodology and computational aspects rather than theory. The students will learn how to apply SAS procedures to data and interpret the results

BIOS 7534 - Data Management for Biostatistics

This course emphasizes data management and software applications using the SAS (Statistical Analysis System) software package. It will introduce the student to SAS codes for: inputting and outputting data, creating temporary and permanent data sets, creating formatted and labeled SAS data sets, merging and connecting SAS data sets, creating output using the TABULATE and REPORT procedures, debugging a SAS program that includes the TABULATE, REPORT and SQL procedures, using characteristic functions in SAS, using a random number generator, probability distributions, arrays, and date and time functions. Students will also write a simple and complex query using the SQL procedure; create, populate and modify a set of tables/views using the SQL procedure; and create a SAS program which includes one or more macros. This course will cover basic relational database design and descriptive statistics in SAS. Particular focus is placed on applications pertaining to public health and biomedical research. 4 credit hours

BIOS 9333 – Applied Longitudinal Data Analysis

This course provides an introduction to longitudinal and clustered data. Topics include the basic concepts of longitudinal data, linear models for longitudinal data, generalized linear models and salient features, generalized estimating equations, generalized linear mixed effects models, missing data and dropouts, sample size and power, repeated measures, and multilevel linear models

BIOS 6531 – Categorical Data Analysis

This course introduces statistical methods for analyzing both univariate and multivariate categorical data and count in medical research and other health-related fields. The course will introduce how to distinguish among the different measurement scales, the commonly used statistical probability distribution and inference methods for categorical and count data. Emphasis will be placed on the application of the methodology and computational aspects rather than theory. The students will learn how to apply SAS procedures to data and interpret the results

BIOS 9333A – Applied Longitudinal Data Analysis

This course provides an introduction to longitudinal and clustered data. Topics include the basic concepts of longitudinal data, linear models for longitudinal data, generalized linear models and salient features, generalized estimating equations, generalized linear mixed effects models, missing data and dropouts, sample size and power, repeated measures, and multilevel linear models

PUBH 7132

This course explores the scientific basis of 21st century disease processes including a survey of the origins, natural history, factors influencing individual and community risk. Clinical symptoms of diseases impacting humans, both acute and chronic, as well as epidemiologic trends will be also be discussed. Students will obtain an understanding of scientific mechanisms associated with the disease processes with particular focus on using this information in health-related professions and public health decision-making. As such, emphasis will be placed on the understanding and application of proposing community-based solutions designed to break the cycle of disease.