<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Causal-Inference on The Standard Error</title><link>https://jongha-jeon-dev.github.io/standarderror/tags/causal-inference/</link><description>Recent content in Causal-Inference on The Standard Error</description><generator>Hugo -- 0.123.7</generator><language>en-gb</language><lastBuildDate>Tue, 13 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://jongha-jeon-dev.github.io/standarderror/tags/causal-inference/index.xml" rel="self" type="application/rss+xml"/><item><title>ML 48: What a Model Relies On Is Not What to Change</title><link>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-48-intervention/</link><pubDate>Tue, 13 Oct 2026 00:00:00 +0000</pubDate><guid>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-48-intervention/</guid><description>Importance and what-if analyses describe the model. In a system with a common cause and a downstream signal, the feature the model relied on most did nothing when changed, and the real lever ranked no higher than a feature with no effect.</description></item><item><title>ML 49: Target the Effect, Not the Risk</title><link>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-49-uplift/</link><pubDate>Tue, 13 Oct 2026 00:00:00 +0000</pubDate><guid>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-49-uplift/</guid><description>A model of who will churn is not a model of whom an offer will keep. Targeting the highest risk did no better than chance; targeting the predicted effect did about twice as well.</description></item></channel></rss>