Biostatistics MA

The Department of Biostatistics educates and trains biostatistical scientists, collaborates with researchers, and conducts methodological research. Department faculty and students work together to develop and apply statistical methods in bioinformatics, epidemiology, public health, and clinical, laboratory, or other health sciences. The rich environment of applications and a full offering of coursework on statistical methods and their theoretical underpinnings, provides a mix of practical training and book knowledge that prepares students for employment in the health industry, government agencies, and research institutions.

Required Core (15 credits)

CHB 550LEC - Pub Hlth Popultn Wellbng Credits: 3
STA 503LEC - Introduction to Applied Statistics I Credits: 3
STA 504LEC - Introduction to Applied Statistics II Credits: 3
STA 521LEC - Intro Theoretical Stat 1 Credits: 3
STA 522LEC - Intro Theoretical Stat 2 Credits: 3
STA 782SEM - Departmental Seminar Credits: 0

Electives (12 credits)

Select 4 from:

STA 509LEC - Statistical Genetics Credits: 3
STA 511LEC - Advanced Statistical Computing Credits: 3
STA 517LEC - Categorical Data Analysis Credits: 3
STA 525LEC - Stats for Bioinformatics Credits: 3
STA 526LEC - Design and Analysis of Clinical Experiments Credits: 3
STA 531LEC - Sample Survys Thery-Meths Credits: 3
STA 536LEC - Statistical Design and Analysis of Experiments Credits: 3
STA 545LEC - Statistical Data Mining I Credits: 3
STA 546LEC - Data Mining II Credits: 3
STA 561LEC - Longitudinal Data Analysis Credits: 3
STA 575LEC - Survival Analysis Credits: 3
STA 581LEC - Multivar Data Analysis Credits: 3

Culminating Experience: Exam and Project or Thesis (0-6 credits)

Complete the comprehensive exam and select either the project or thesis option.

Students pursuing the thesis may complete 1 less elective course and register for 6 credits of thesis.

STA 700TUT - Thesis Guidance Credits: 1 - 16

Total Credit Hours: 30

3.0 Degree GPA required

SED Statement

This program is officially registered with the New York State Education Department (SED).

Program Learning Outcomes (PLOs)

1) Describe advanced concepts of probability, random variation and commonly used statistical probability distributions.

2) Develop an efficient design for collecting, recording, and storing data collected in the conduct of public health and medical research.

3) Develop sample size and statistical power calculations for basic study designs including those utilized in clinical trials.

4) Design efficient computer programs for study management, statistical analysis, as well as presentation using SAS and other programming languages.

5) Produce edited data sets suitable for statistical analyses. Apply advanced informatics techniques with vital statistics and public health records in the description of public health characteristics and in public health research and evaluation.

6) Perform analyses of stated hypotheses using a variety of analytical tools including analysis of variance, multiple regression, nonparametric statistics, logistic regression, multivariate analyses, and methods for analyzing rates and failure time data. Interpret results of advanced statistical analyses and use these results to make relevant inferences from data.

7) Produce working tables and statistical summaries describing research in health science.

8) Develop written presentations based on intermediate to advanced statistical analyses for both public health professionals and educated lay audiences.

9) Develop oral presentations based on intermediate to advanced statistical analyses for both public health professionals and educated lay audiences.

10) Our students will be well prepared to apply successfully for graduate programs or jobs.