Year Published: 2013

Time to Complete: 65 min

Instructor: Lori Lyn Price, MAS

Learning Level: Fundamental

Primary Audience: Researchers

Prerequisite: None

Skills Domain: Scientific Concepts and Research Design


What is linear and logistic regression, and when should you use it?

In this course, Statistician Lori Lyn Price, MAS, will explain how to decide when regression should be used, and when linear or logistic regression is most appropriate. She will also discuss basic assumptions, modeling strategies, and how to interpret the results of regression models.

Learning Objectives

After completing this course, you will be able to:

  • Determine when regression should be used
  • Describe the differences between linear and logistic regression
  • Discuss basic assumptions of linear and logistic regression
  • Identify the advantages of regression models
  • Interpret the results of regression models

Content Outline

  • Linear & Logistic Regression XY for Exposure and Outcome
  • Regression Equation
  • Pearson Correlation
  • Influential Points
  • Hypothesis Testing
  • Regression Methods
  • Summary of Linear Regression and Q&A
  • Study Investigation
  • Odds Ratios
  • Logistic Regression
  • Multivariable Analysis
  • Interaction
  • Modeling Strategies
  • Potential Risk Factors
  • Take Home Message

Resources

  • Lecture Slide Deck (PDF)

Course Evaluation

  • Post-Course Evaluation
  • Course Completion Verification
 This Course is Free