Simple Regression Analysis in Public Health

Instructor: John McGready, PhD, MS

Beginner Level • 1 week to complete at 10 hours a week • Flexible Schedule

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

Data analysis
Quantitative Research
Statistical Inference
Probability & Statistics
Statistical Analysis
Epidemiology
Biostatistics
Statistical Methods
Regression Analysis
Public Health

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

Module one covers simple regression, the four different types of regression, commonalities between them, and simple linear aggression. Before completing the graded quiz, you can test your knowledge with the practice quiz.

Within module two, we will look at logistic regression, create confidence intervals, and estimate p-values. You will have the opportunity to test your knowledge in both a practice quiz and a graded quiz.

Module three focuses on Cox regression with different predictors. You will have the opportunity to test your knowledge first with the practice quiz and, then, with the graded quiz.

Within module four, you will look at confounding and adjustment, and unadjusted and adjusted association estimates. Additionally, you will learn about effect modification. Similar to previous modules, you will first take a practice quiz before completing the graded quiz.

During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about self-administration of injectable contraception and one about medical appointment scheduling in Brazil. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken other courses in this specialization, then this scenario will be familiar.