4 min listen
[MINI] Conditional Independence
FromData Skeptic
ratings:
Length:
15 minutes
Released:
Jul 21, 2017
Format:
Podcast episode
Description
In statistics, two random variables might depend on one another (for example, interest rates and new home purchases). We call this conditional dependence. An important related concept exists called conditional independence. This phrase describes situations in which two variables are independent of one another given some other variable. For example, the probability that a vendor will pay their bill on time could depend on many factors such as the company's market cap. Thus, a statistical analysis would reveal many relationships between observable details about the company and their propensity for paying on time. However, if you know that the company has filed for bankruptcy, then we might assume their chances of paying on time have dropped to near 0, and the result is now independent of all other factors in light of this new information. We discuss a few real world analogies to this idea in the context of some chance meetings on our recent trip to New York City.
Released:
Jul 21, 2017
Format:
Podcast episode
Titles in the series (100)
Introduction: The Data Skeptic Podcast features conversations with topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the... by Data Skeptic