.. Econometrics Navigator documentation master file, created by 
   sphinx-quickstart on Fri Nov 16 05:36:08 2018.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

.. toctree::
   :maxdepth: 1
   
   topics/index.rst
   textbook/index.rst
   how-to-teach.md
   data.md
   software.rst
   tweets.md 
   blogs.md
   acronyms.md
   roadmap.md

Welcome to Econometrics Navigator!
==================================

Goals
-----

The Econometrics Navigator (EN) goal is to make quality instruction in 
statictics and econometrics accessible.

Types of content
----------------

- Open access textbooks and community knowledge with personal touch 
  (reddit, StackOverflow, Twitter threads).
- Minimal code examples in Python, R, gretl or Julia to try things fast.
- Datasets and cases for quantative analysis.
- Ideas on how to structure the learning paths.

1. Own articles
~~~~~~~~~~~~~~~

The articles are in `Concepts and techniques section <topics/index.rst>`__,  
organised alphabetically. Finished examples are:

- `Maximum likelihood <topics/max-likelihood.html>`__
- `Bootstrap <topics/bootstrap.html>`__
- `ANOVA <topics/anova.html>`__

2. Textbooks guide  
~~~~~~~~~~~~~~~~~~

`Textbooks review <textbook/index.html>`__ attempts to sort out and annotate textbooks and 
references by several categories, starting from math preliminaries and up to ML/DL 
applications.

In econometrics the categories are 'general' textbooks, cross-section/panel, time series 
and bayesian texts. Whatever I could not document well, I did put in the 
`mindmap <textbook/mindmap.html>`__ section.

The backstage workings of the Navigator are `History of econometrics <textbook/history.html>`__, 
`Ways to review econometrics <textbook/ways-into-econometrics.html>`__. 

Review of resources about mathematic statistics is still a `draft <textbook/statistics.html>`__.

3. Better teaching
~~~~~~~~~~~~~~~~~~

These documents organise thinking about better teaching of 
econometrics in terms of sequence of topics, better analogies 
for the learner and a faster bridge to coding and working 
with real data from formulas and concepts. Specifically I collected
the links about `technical pedagogy here <textbook/how-to-teach.html>`__.


Twitter 
-------

So far twitter has been an enormously valuable source of demos, links and opinion for me.
I keep a `separate page with twitter posts <tweets.html>`__, some of my favorites are:

- `Undergrad Econometrics Cheatsheet <https://twitter.com/tyleransom/status/1085242403643183105>`__ by Tyler Ransom

.. raw:: html

    <embed>
    <blockquote class="twitter-tweet"><p lang="en" dir="ltr">Also, in case it&#39;s useful, here is an entire overview of undergrad econometrics (no matrix algebra) in 3 pages: <a href="https://t.co/kQYrn92v7w">https://t.co/kQYrn92v7w</a> <a href="https://t.co/UBe7OZJTJh">pic.twitter.com/UBe7OZJTJh</a></p>&mdash; Tyler Ransom (@tyleransom) <a href="https://twitter.com/tyleransom/status/1085242403643183105?ref_src=twsrc%5Etfw">January 15, 2019</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
    </embed>

- `Casual graphs and XY plane animations <http://nickchk.com/causalgraphs.html>`__ by Nick Huntington-Klein

.. raw:: html

    <embed>
    <blockquote class="twitter-tweet"><p lang="en" dir="ltr">As requested, slower graphs! Also added a graph on collider bias, the webpage explanation helps there.<br><br>These graphs are intended to show what standard causal inference methods actually *do* to data, and how they work.<br><br>This is what controlling for a binary variable looks like: <a href="https://t.co/dTZxqY5JxA">pic.twitter.com/dTZxqY5JxA</a></p>&mdash; Nick HK (@nickchk) <a href="https://twitter.com/nickchk/status/1068215492458905600?ref_src=twsrc%5Etfw">November 29, 2018</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
    </embed>

- `Investigative time series example <https://twitter.com/PogrebnyakE/status/1111897245362909185>`__ by @cubic_logic 

.. raw:: html

    <embed>
    <blockquote class="twitter-tweet"><p lang="en" dir="ltr">Two series. Find which one is a random walk. <a href="https://t.co/IC8QxzhVND">pic.twitter.com/IC8QxzhVND</a></p>&mdash; (λ --- --. .. -.-.)³ (@cubic_logic) <a href="https://twitter.com/cubic_logic/status/1111346696754249730?ref_src=twsrc%5Etfw">March 28, 2019</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
    </embed>

- `Common statistical tests are linear models (or: how to teach stats) <https://lindeloev.github.io/tests-as-linear>`__ by Jonas Kristoffer Lindeløv

.. raw:: html

    <embed>
    <blockquote class="twitter-tweet"><p lang="en" dir="ltr">I&#39;ve made this cheat sheet and I think it&#39;s important. Most stats 101 tests are simple linear models - including &quot;non-parametric&quot; tests. It&#39;s so simple we should only teach regression. Avoid confusing students with a zoo of named tests. <a href="https://t.co/9PFR1ly3lW">https://t.co/9PFR1ly3lW</a> 1/n</p>&mdash; Jonas K. Lindeløv (@jonaslindeloev) <a href="https://twitter.com/jonaslindeloev/status/1110907133833502721?ref_src=twsrc%5Etfw">March 27, 2019</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
    </embed>


Changelog
---------

Changelog and future steps outlined are outlined in `roadmap <roadmap.html>`__.


Contacts
--------

This publication is edited by `@PogrebnyakE <https://twitter.com/PogrebnyakE>`__.


Source
------

The source of this publication is available at https://github.com/epogrebnyak/econometrics-navigator
and the short URL for this page is https://tinyurl.com/emnavig.