Department of Biostatistics & Data Science

Biostat Courses

• Biostatistics

  Course Number: BIOS 6343

  Description:
  This course introduces the general application of biostatistical analysis, as performed in the biomedical, public health and social sciences. The course will examine how a wide variety of problems can be described and analyzed using the language of statistics. Specific topics to be covered include:

  • probability and distributions, data types, graphical representation of data, and the connection of probability to statistics and statistical inference;
  • hypothesis testing, equivalence testing, one vs. two sided tests;
  • parametric bivariate statistics such as the t-test and chi-squared tests, and their appropriate application, as well as non-parametric alternatives;
  • parametric multivariate statistics such as ANOVA, the regression framework including linear and logistic

  The aim of the course is fourfold. First, to familiarize students with the vocabulary, basic notions, and some general concepts of statistics. Second, to apply these techniques to real data sets, using statistical programming software. Third, to learn how to use a statistical software programming language for data manipulation and analysis, and to gain a general understanding of statistical software tools. Fourth, to critically analyze both the results of our own analyses, as well as published work in the biomedical literature.
  
  Credit: 3

  Required by MS: Yes

  Required by MPH: Yes

• Introduction to Linear Models

  Course Number: BIOS 6344

  Description:

  This course provides an introduction to the most common statistical model used in data analysis. The model has been adopted as a conceptual framework throughout the biomedical, public health and social sciences. It includes special cases: simple regression and correlation, multiple regression, analysis of covariance and analysis of variance. The model is termed as linear model and with broad assumptions, and uses simple computational techniques known as ordinary least squares. The course will cover assumptions and diagnostic methods of these models. Examples from the biomedical and socio-medical sciences will illustrate all of the techniques. Computations require using the computer package SAS. The interpretation and presentation of results are emphasized.

  Credit: 3

  Required by MS: Yes

  Required by MPH: Yes

  Prerequisite: BIOS 6343 Biostatistics, BIOS 6143 Data Management

• Categorical Data Analysis

  Course Number: BIOS 6341

  Description:

  This course surveys theory and methods for the analysis of categorical response and count data. The course begins with an overview of classic results and likelihood based inference for categorical data analysis (chi-square statistics). We will then examine appropriate methods for dealing with contingency tables. Additional topics include logistic regression, model building strategies, multiple logistic regression, poisson regression, Loglinear Models, Multicategory Logit Models, and Models for Matched Pairs.

  Credit: 3

  Required by MS: Yes

  Required by MPH: Yes

  Prerequisite: BBSC 6222 Biostatistics or BIOS 6343 Biostatistics or BIOS 6347, BIOS 6344 Introduction to Linear Models

• Correlated Data Analysis

  Credit: 3

  Required by MS: Yes

  Required by MPH: No

• Survival Analysis

  Course Number: BIOS 6321

  Description:

  This course aims to begin a dialogue that will continue throughout the students’ careers: that between technical statistical knowledge, and the real world application thereof, in collaboration with non-statistically oriented content experts. The matter of the course details sundry aspects of this conversation: the overarching systems within which statistical consulting takes place, the personal relationships between the client and consultant, the technical details of statistical analysis and their explanation to clients, and miscellany including an aside into graphical representation of statistical information.
  
  This material will be supplemented with lectures from experts: those who have consulted in non-academic areas of the biomedical sciences, those who have consulted in other fields, and those who are our partners in this endeavor – our consulting clients.

  Credit: 3

  Required by MS: Yes

  Required by MPH: Yes

  Prerequisite: BIOS 6343 Biostatistics, BIOS 6344 Introduction to Linear Models, BIOS 6143 Data Management

• Data Management

  Course Number: BIOS 6143

  Description:

  This course introduces the management of data using SAS programming language. The course content includes how to read, clean, analyze data and generate outputs. The data and proc steps in SAS will be presented. The course will also review some basic data exploration methods. The emphasis of this course is to get students acquainted with the required skill not only to perform independent data analysis using SAS but also to advance their programming skills after the course.

  Credit: 1

  Required by MS: Yes

  Required by MPH: Yes

• Research/Practicum

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Introduction to Probability Theory

  Credit: 3

  Required by MS: Yes

  Required by MPH: No

• Survey Methods

  Course Number: PHS 6374

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Introduction to Machine Learning

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Introduction to Big Data Visual Analytics

  Credit: 2

  Required by MS: No

  Required by MPH: No

• Statistical Consulting

  Course Number: PHS 6242

  Description:

  This course aims to begin a dialogue that will continue throughout the students’ careers: that between technical statistical knowledge, and the real world application thereof, in collaboration with non-statistically oriented content experts. The matter of the course details sundry aspects of this conversation: the overarching systems within which statistical consulting takes place, the personal relationships between the client and consultant, the technical details of statistical analysis and their explanation to clients, and miscellany including an aside into graphical representation of statistical information.
  
  This material will be supplemented with lectures from experts: those who have consulted in non-academic areas of the biomedical sciences, those who have consulted in other fields, and those who are our partners in this endeavor – our consulting clients.
  
  Evaluation of students in terms of achieving core MPH competencies and meeting course learning objectives will be done through in class assignments and discussion. Consultation is a group activity, not a solo one; this group activity is at the core of the collaboration central to an MPH and modern scientific endeavor. Assessment of many aspects of an individual’s abilities in this area is thus necessarily done in the social context of a lecture, rather than a solitary one.

  Credit: 2

  Required by MS: Yes

  Required by MPH: Yes

• Clinical Trials

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Health Services Research Analysis

  Description:

  This course will introduce the analytical methods commonly used in health services research. Students will be able to carry out most statistical analyses discussed in the course with SAS. Topics include interrupted time-serial analysis, difference-in-difference, regression discontinuity, propensity score methods, matching, the parametric g-formula, inverse probability weighting of marginal structural model, instrumental variable analysis, and decision analysis.

  Credit: 2

  Required by MS: No

  Required by MPH: No

  Prerequisite: BIOS 6143 Data Management, BIOS 6343 Biostatistics, BIOS 6344 Introduction to Linear Model, BIOS 6321 Survival Data Analysis

Non-Biostat Courses

• Introduction to Epidemiology

  Course Number: EPI 6330

  Description:

  This course is an introduction to the theory and practice of epidemiology, the study of the distribution and determinants of health in populations and the application of this study to control and improve health outcomes. Concepts that will be covered include: historical foundations of epidemiologic research, measures of disease frequency, standardization, study design, measures of effect, screening, and causality. The student will gain insight into the strengths and limitations of population-based research, acquire skills to critically evaluate epidemiologic research, understand the basis of causal inference regarding health and disease, and appreciate the scope of epidemiology and its uses in the areas of public health and clinical care.

  Credit: 3

  Required by MS: No

  Required by MPH: Yes

• Foundations of Medical Informatics

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Biomedical Informatics: Applied

  Credit: 3

  Required by MS: No

  Required by MPH: No

• Epidemiology Methods

  Course Number: PHS 6333

  Description:

  This course builds on PHS 6330 “Introduction to Epidemiology” offered in the Fall of the previous year. Advanced topics in the theory and practice of epidemiologic research and public health practice will be covered during this course, which include development of epidemiologic methods, issues with study design, eliminating bias, assessing and controlling for confounding, effect modification/interaction, matching, misclassification, cross-sectional, case-control, cohort studies, clinical trials, systematic reviews and meta-analysis.

  Credit: 3

  Required by MS: No

  Required by MPH: No

  Prerequisite: BIOS 6343 Biostatistics, BIOS 6143 Data Management, EPI 6330 Introduction to Epidemiology

• Research Rotation

  Credit: 3

  Required by MS: Yes

  Required by MPH: No

• Analytical Methods in Public Health

  Course Number: SPPH 6496-006

  Description:

  This course is designed to provide an overview of analytical methods in public health, both quantitative and qualitative. Students will learn basics of epidemiological study design, basic quantitative and qualitative analysis, data collection, and interpretation.

  Credit: 4

  Required by MS: No

  Required by MPH: Yes

• PH Assessment, Planning & Evaluation

  Course Number: PHS 6324

  Credit: 3

  Required by MS: No

  Required by MPH: Yes

• Public Health Practice Experience

  Course Number: SPPH 6070

  Credit: 4

  Required by MS: No

  Required by MPH: Yes

• Policy & Equity

  Course Number: SPPH 6469

  Description:

  The Policy and Equity course will enable students to evaluate and recommend policies for a selected issue, apply advocacy products or plans for the selected issue, and apply the policy-making process for the issue. Students will compare and contrast health systems’ models at the global level, including how values and culture affect these systems and the policies that create or change these systems. Students will identify historical and present-day factors (e.g., social, systemic, organizational, community) that contribute to health inequities and obstruct achieving health equity, and develop a systems map identifying multi-level causes, including structural bias, social inequities, and racism, for the public health or health-related issue.

  Credit: 4

  Required by MS: No

  Required by MPH: Yes

• Integrative Learning Experience

  Course Number: SPPH 6016

  Description:

  The Integrative Learning Experience (ILE) is a requirement of all MPH students. The ILE is a culminating project that allows students to integrate the knowledge and skills they have gained throughout their MPH coursework and practice experience. It is intended to provide students with the opportunity to explore a public health area of interest in greater depth, produce a high-quality written product that aligns with their educational and professional goals, and demonstrate the synthesis of competencies attained during the MPH program.

  Credit: 3

  Required by MS: No

  Required by MPH: Yes

• Applied Public Health Leadership

  Course Number: SPPH 6338

  Credit: 3

  Required by MS: No

  Required by MPH: Yes

• MPH Public Health Ethics

  Course Number: BHH 6137

  Credit: 1

  Required by MS: No

  Required by MPH: Yes