BIOSTAT592: Applied Regression
- Graduate level
- Both Online MPH and Online MS
- This is a first year course for Online students
- Spring-Summer term(s) term for online MPH students; Spring-Summer term(s) term for online MS students.
- 3 Credit Hour(s) for online MPH students for residential students; 3 Credit Hour(s) for online MS students
- Instructor(s): Kidwell, Kelley (Online MPH); Kidwell, Kelley (Online MS);
- Prerequisites: BIOSTAT 501, BIOSTAT 591
- Advisory Prerequisites: None
- Description: This course is designed to introduce linear regression using multiple variables to predict a continuous outcome. This course emphasizes the application of multiple linear regression to substantive public health problems focusing on interpretation and inference. We use RStudio to analyze public health datasets, evaluate regression assumptions, and assess model fit.
- Learning Objectives: 1. Explain the critical importance of evidence in advancing public health knowledge 2. Interpret results of data analysis for public health research, policy or practice
|Department||Program||Degree||Competency||Specific course(s) that allow assessment||Population and Health Sciences||MPH||Compare population health indicators across subpopulations, time, and data sources||PUBHLTH515, BIOSTAT592, EPID590, EPID592, EPID643, BIOSTAT595, BIOSTAT501||Population and Health Sciences||MPH||Estimate population health indicators from high quality data resources from diverse sources||PUBHLTH515, EPID643, NUTR590, BIOSTAT592, BIOSTAT501|