Exploring “Correlation Does Not Imply Causation” in Introductory Statistics

 Exploring “Correlation Does Not Imply Causation” in Introductory Statistics
Poster Presentation Time: 1225-1400; 1500-1600
Venue: K4, Tai Po-Shek-O Room, Lower Level I
Presenter(s)

– Dr Kin Yat LIU, Lecturer, Statistics, The Chinese University of Hong Kong

Abstract

“Correlation does not imply causation” is an important concept that is included in almost all introductory statistics courses. Comprehending this concept is crucial for students to grasp advanced statistical concepts like multivariate analysis, Simpson’s paradox, and causal inference. However, the intricacies of this principle are often not explored in depth. To address this, we employ simulated experiences and the use of Monte Carlo simulation to provide students with an understanding of the significance and fundamental nature of the idea that “correlation does not imply causation.”

Theme: 1. Showcase Project Achievements
Sub-theme: 1.4  Other UGC grants, Quality Education Fund (QEF), and Quality Enhancement Support Scheme (QESS)