Simple Regression Analysis in Public Health

This course is part of Biostatistics in Public Health Specialization

Instructor: John McGready, PhD, MS

What you'll learn

  •   Practice simple regression methods to determine relationships between an outcome and a predictor
  •   Recognize confounding in statistical analysis
  •   Perform estimate adjustments
  • Skills you'll gain

  •   Regression Analysis
  •   Biostatistics
  •   Quantitative Research
  •   Statistical Analysis
  •   Statistical Methods
  •   Epidemiology
  •   Statistical Inference
  •   Public Health
  •   Data Analysis
  •   Probability & Statistics
  • There are 5 modules in this course

    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.

    Simple Logistic Regression

    Simple Cox Proportional Hazards Regression

    Confounding, Adjustment, and Effect Modification

    Course Project

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