Jul 08, 2020
 HELP 2019-2020 Undergraduate Academic Catalog [ARCHIVED CATALOG] Print-Friendly Page (opens a new window)

# MA 3611 - Biostatistics

3 lecture hours 0 lab hours 3 credits
Course Description
This course provides an introduction to biostatistics for biomedical engineering students. As a result of this course the students are expected to understand and prepare statistical analyses of data from physiological systems in the laboratory and clinical environment. Students learn basic probability theory that includes discrete and continuous probability distributions. They learn how to apply that theory to hypothesis testing and understand the difference between a z-test and t-test, one- and two-sample inference hypothesis testing, and Analysis of Variance. Additional concepts covered include hypothesis formulation and testing, both parametric and nonparametric. Either the statistical package SAS or the statistical package SPSS will be introduced to the students and will be used to perform statistical analyses.  Finally, journal articles from the New England Journal of Medicine (NEJM) containing significant statistical components will be considered in class. (prereq: MA 136 ) (coreq: MA 137 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Recognize and evaluate conditional probability situations such as Bayes’ Rule, specificity, sensitivity, predictive value positive, and predictive value negative
• Set up and evaluate inferences using hypothesis tests and confidence intervals
• Perform hypothesis tests for one- and two-sample situations
• Recognize when analysis of variance (ANOVA) is applicable, and subsequently be able to apply and evaluate ANOVA calculations
• Recognize when nonparametric situations are present and then be able to apply the correct nonparametric test, evaluate it, and interpret it
• Use SAS (or SPSS if it is the statistical package being used) when appropriate
• Read and interpret the statistical content of assigned articles in the NEJM

Prerequisites by Topic
• None

Coordinator
Dr. Kseniya Fuhrman