4. Model :: intro
In model basics,
you’ll learn how models work mechanistically, focusing on the important family of linear models.
You’ll learn general tools for gaining insight into what a predictive model tells you about your data, focusing on simple simulated datasets.
In model building,
you’ll learn how to use models to pull out known patterns in real data.
Once you have recognized an important pattern, it’s useful to make it explicit in a model, because then you can more easily see the subtler signals that remain.
In many models,
you’ll learn how to use many simple models to help understand complex datasets.
This is a powerful technique, but to access it you’ll need to combine modelling and programming tools.
All models are wrong, but some are useful.
Model의 궁극적인 목적은 데이터셋에 대해 단순한 저차원의 요약을 제공하는 것이다.
데이터를 pattern과 residual로 구분하기 위해 Model을 사용한다.