From ca818726fc902ce1ac4b05d26f21d65f9d6513d0 Mon Sep 17 00:00:00 2001 From: hadley Date: Wed, 3 May 2017 07:55:03 -0500 Subject: [PATCH] Improve intro Fixes #480 --- model-building.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/model-building.Rmd b/model-building.Rmd index 68e5d4d..3d8b384 100644 --- a/model-building.Rmd +++ b/model-building.Rmd @@ -2,7 +2,7 @@ ## Introduction -In the previous chapter you learned how linear models worked, and learned some basic tools for understanding what a model is telling you about your data. The previous chapter focussed on simulated datasets to help you learn about how models work. This chapter will focus on real data, showing you how you can progressively build up a model to aid your understanding of the data. +In the previous chapter you learned how linear models work, and learned some basic tools for understanding what a model is telling you about your data. The previous chapter focussed on simulated datasets. This chapter will focus on real data, showing you how you can progressively build up a model to aid your understanding of the data. We will take advantage of the fact that you can think about a model partitioning your data into pattern and residuals. We'll find patterns with visualisation, then make them concrete and precise with a model. We'll then repeat the process, but replace the old response variable with the residuals from the model. The goal is to transition from implicit knowledge in the data and your head to explicit knowledge in a quantitative model. This makes it easier to apply to new domains, and easier for others to use.