Abstract
As a fundamental concept in scientific inquiry, causality addresses the central problem of cause and effect relationships, which sets it apart from statistics. Causality explores the complex mechanisms underlying these observed relationships, whereas statistics focuses primarily on the quantitative analysis of data to find patterns, associations, and correlations. It seeks to determine the direction of influence by offering a strict framework to determine the underlying causes of events as well as their co-occurrence. To put it simply, causality takes empirical research to a higher level by attempting to identify the underlying ideas that underpin the complex interactions between variables and phenomena. This leads to a more thorough and accurate understanding of the natural world.
Reza Rahimi Azghan
Grad Research Associate
I am a Ph.D. student at Arizona State University. I work as a Graduate Research Associate at Embedded Machine Intelligence Lab (EMIL) under the supervision of Dr. Hassan Ghasemzadeh.