MATH 351 Biostatistics

5 credits

This course provides an introduction to statistical analysis of bio-medical data. Topics include descriptive statistics, probability, inferential statistics, reliability, confidence intervals, power analysis, hypothesis testing, correlation, regression, ANOVA, and nonparametric methods.

This course meets the Quantitative Reasoning general education distribution requirement.

Prerequisites: MATH& 146 and admission to the BAS in Public Health program

Course Outcomes
Upon successful completion of this course students will be able to:

Characterize central tendency and variability of data using descriptive statistics
Characterize data distribution
Analyze types of error in collecting and interpreting statistical data
Calculate sensitivity, specificity, predictive values and confidence intervals
Calculate the statistical power and sample size
Perform one- and two-sample inference using appropriate parametric and nonparametric statistical methods
Apply statistical regression models to biological data sets, and describe the validity of those models
Describe, graph and compute correlation coefficients
Perform multi-sample inference using ANOVA
Analyze real biomedical data sets and write a scientific paper describing the analysis

College-Wide Learning Outcomes
This course teaches to the college-wide learning outcome of Critical Thinking, the ability to evaluate information, draw inferences, arrive at conclusions, and create solutions based on objective analysis of the evidence.

Total Hours: 50 Theory (Lecture) Hours: 50