Simple Regression Analysis in Public Health

Coursera Simple Regression Analysis in Public Health

Platform
Coursera
Provider
Johns Hopkins University
Effort
3-4 hours a week
Length
4 weeks
Language
English
Credentials
Paid Certificate Available
Part of
Course Link
Overview
Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between an outcome of interest and a single predictor via a linear equation. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include logistic regression, confidence intervals, p-values, Cox regression, confounding, adjustment, and effect modification.

WHAT YOU WILL LEARN
  • Practice simple regression methods to determine relationships between an outcome and a predictor
  • Recognize confounding in statistical analysis
  • Perform estimate adjustments
Syllabus
  1. Simple Regression Methods
  2. Simple Logistic Regression
  3. Simple Cox Proportional Hazards Regression
  4. Confounding, Adjustment, and Effect Modification
  5. Course Project

Taught by
John McGready, PhD, MS
Author
Coursera
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