From e1259144abc174c7bc4aacda0bab3578c92d7b24 Mon Sep 17 00:00:00 2001
From: Donne Martin <donne.martin@gmail.com>
Date: Sat, 4 Jul 2015 08:36:49 -0400
Subject: [PATCH] Moved statistical inference section below scikit-learn
 section.

---
 README.md | 30 +++++++++++++++---------------
 1 file changed, 15 insertions(+), 15 deletions(-)

diff --git a/README.md b/README.md
index e95d09a..dcf8ba5 100644
--- a/README.md
+++ b/README.md
@@ -21,10 +21,10 @@ This repo is a collection of IPython Notebooks I reference while working with da
 * [amazon web services](#aws)
 * [kaggle-and-business-analyses](#kaggle-and-business-analyses)
 * [scikit-learn](#scikit-learn)
+* [statistical-inference-scipy](#statistical-inference-scipy)
 * [pandas](#pandas)
 * [matplotlib](#matplotlib)
 * [numpy](#numpy)
-* [statistical-inference-scipy](#statistical-inference-scipy)
 * [python-data](#python-data)
 * [command lines](#commands)
 * [misc](#misc)
@@ -114,6 +114,20 @@ IPython Notebook(s) demonstrating scikit-learn functionality.
 | [gmm](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scikit-learn/scikit-learn-gmm.ipynb) | Gaussian mixture models. |
 | [validation](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scikit-learn/scikit-learn-validation.ipynb) | Validation and model selection. |
 
+<br/>
+<p align="center">
+  <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/scipy.png">
+</p>
+
+## statistical-inference-scipy
+
+| Notebook | Description |
+|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| scipy | SciPy is a collection of mathematical algorithms and convenience functions built on the Numpy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. |
+| [effect_size](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/effect_size.ipynb) | Effect size. |
+| [sampling](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/numpy.ipynb) | Random sampling. |
+| [hypothesis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/numpy.ipynb) | Hypothesis testing. |
+
 <br/>
 <p align="center">
   <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/pandas.png">
@@ -154,20 +168,6 @@ IPython Notebook(s) demonstrating NumPy functionality.
 |--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | [numpy](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/numpy/numpy.ipynb) | Adds Python support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays. |
 
-<br/>
-<p align="center">
-  <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/scipy.png">
-</p>
-
-## statistical-inference-scipy
-
-| Notebook | Description |
-|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| scipy | SciPy is a collection of mathematical algorithms and convenience functions built on the Numpy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. |
-| [effect_size](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/effect_size.ipynb) | Effect size. |
-| [sampling](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/numpy.ipynb) | Random sampling. |
-| [hypothesis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/scipy/numpy.ipynb) | Hypothesis testing. |
-
 <br/>
 <p align="center">
   <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/python.png">