JMP Pro 19 Causal Treatment Models
Автор: JMP Statistical Discovery
Загружено: 2026-01-06
Просмотров: 146
Описание:
Causal inference is the process of determining whether and how a treatment, intervention, or exposure causes a change in an outcome, rather than just being associated with it. Causal inference can be useful when designed experiments and randomized controlled trials (RCTs) are not feasible.
The JMP Pro 19 Causal Treatment Models estimates causal effects using observational data.
00:00:00 Introduction
01:40:25 Overview of Data Used in the Demo
02:10:00 Examining and Comparing Distributions Across Variables
03:55:00 Predictor Screening and Lasso Model Views
04:35:00 Creating Causal Treatment Models and Interpreting Results
Learn more about how to use Causal Treatment Models in JMP Pro: hhttps://www.jmp.com/support/help/en/1...
Повторяем попытку...
Доступные форматы для скачивания:
Скачать видео
-
Информация по загрузке:
![Как внимание стало настолько эффективным [GQA/MLA/DSA]](https://imager.clipsaver.ru/Y-o545eYjXM/max.jpg)
