diff --git a/_includes/package-nav.html b/_includes/package-nav.html
index ac2f1cf..1aa1fd6 100644
--- a/_includes/package-nav.html
+++ b/_includes/package-nav.html
@@ -4,7 +4,9 @@
Visualize
Transform
Tidy
+Model
Import
+Exploratory data analysis
R Markdown
@@ -12,13 +14,11 @@
Data structures
+Expressing yourself with code
Strings
Dates and times
-Expressing yourself with code
Lists
-Linear models
Models and visualisation
-Model assesment
-Other models
+Model assessment
diff --git a/eda.Rmd b/eda.Rmd
new file mode 100644
index 0000000..a66c46b
--- /dev/null
+++ b/eda.Rmd
@@ -0,0 +1,5 @@
+---
+layout: default
+title: Exploratory data analysis
+output: bookdown::html_chapter
+---
diff --git a/model-assess.Rmd b/model-assess.Rmd
index 5594e00..f7e3f00 100644
--- a/model-assess.Rmd
+++ b/model-assess.Rmd
@@ -10,6 +10,9 @@ set.seed(1014)
options(digits = 3)
```
+* Some discussion of p-values.
+* Bootstrapping to understand uncertainty in parameters.
+* Cross-validation to understand predictive quality.
## Multiple models
diff --git a/model-other.Rmd b/model-other.Rmd
deleted file mode 100644
index 23b0d69..0000000
--- a/model-other.Rmd
+++ /dev/null
@@ -1,24 +0,0 @@
----
-layout: default
-title: Other model familes
-output: bookdown::html_chapter
----
-
-
-[Applied Predictive Modeling](http://amzn.com/1461468485).
-[An Introduction to Statistical Learning](http://amzn.com/1461471370)
-
-
-## Extensions of linear models
-
-* Generalised linear models: logistic, ...
-
-* Hierarchical models
-
-## Non-linear
-
-* Random forrests
-
-## Clustering
-
-Show example of clustering babynames by year.
diff --git a/model-linear.Rmd b/model.Rmd
similarity index 50%
rename from model-linear.Rmd
rename to model.Rmd
index 15f52ea..59507f5 100644
--- a/model-linear.Rmd
+++ b/model.Rmd
@@ -18,3 +18,19 @@ Review caret and mlr.
* Interactions
* Splines
* Log transform
+
+
+[Applied Predictive Modeling](http://amzn.com/1461468485).
+[An Introduction to Statistical Learning](http://amzn.com/1461471370)
+
+# Other model families
+
+List of important classes on modelling; paragraph about why it's useful/different to lm, and a pointer to where to learn more.
+
+* Generalised linear models: logistic, ...
+
+* Hierarchical models
+
+* Random forrests
+
+* Unsupervised techniques