Computer Labs 
**************

.. admonition:: Julia in VS Code

    We will be working with the Julia programming language this semester. I like Julia because it is
    good with linear algebra and also let's us do Monte Carlo simulations quite smoothly. Also, it's
    free!


Preparing your computer
========================

To prepare your computer for the semester, follow these steps:

* Go to https://julialang.org/downloads and install the latest version of Julia on your machine.

  (Random note: If your computer runs on Windows 7, use Julia version 1.5.x)

* Go to https://code.visualstudio.com/download and install VS Code on your machine.

* Open VS Code and install the ``Julia`` extension and the ``Jupyter`` extension. (It's easy to
  install extensions within VS Code, just have a look through the documentation.)

* If you like, write me (Juergen) an email and let me know if and how it worked. Definitely drop me
  a line if you haven't been successful! 




Week 2 
=======

The Julia notebook for week 2 will be posted here soon. Once you have a working Julia environment in
VS Code, you can try and see if you are able to open the notebook file.

*   :download:`Julia notebook for week 2 <../notebooks/students/week_2.ipynb>`

Open it in VS Code.


Week 3
======

Continue your work on last week's notebook. Once you're done, work on this:

*   :download:`Julia notebook for week 3 <../notebooks/students/week_3.ipynb>` 

*   :download:`Card data set <../notebooks/wending/data/card.csv>` 

*   :download:`Card data set description <../notebooks/data/card.des>`

Week 4
======

Finish your work on last week's notebook. Once you're done, work on this:

*   :download:`Julia notebook for week 4 <../notebooks/students/week_4.ipynb>` 

Week 5
======

This week you will continue your work on the WLLN and you will also simulate the central limit
theorem.

*   :download:`Julia notebook for week 5 <../notebooks/students/week_5.ipynb>` 

Week 6
======

This week you will revisit Card's earnings/schooling data set and do some IV estimation.

*   :download:`Julia notebook for week 6 <../notebooks/students/week_6.ipynb>` 

Week 7
======

This week you will run some Monte Carlo simulations. We're creating our own data set and see how
close the estimator is to the true parameter (of our own choosing).

*   :download:`Julia notebook for week 7 <../notebooks/students/week_7.ipynb>` 

Week 8
======

Continue your Monte Carlo simulations from last week.

*   :download:`Julia notebook for week 8 <../notebooks/students/week_8.ipynb>` 

Week 9
======

This week's lab is very similar to your computational assignment.

*   :download:`Julia notebook for week 9 <../notebooks/students/week_9.ipynb>` 

Week 10
=======

This week you are coding an MLE optimization problem.

*   :download:`Julia notebook for week 10 <../notebooks/students/week_10.ipynb>` 

Week 11
=======

This week you are implementing probit/logit estimation of limited dependent variable models.

*   :download:`Julia notebook for week 11 <../notebooks/students/week_11.ipynb>` 

*   :download:`Mroz data set <../notebooks/data/mroz.csv>` 

*   :download:`Mroz data set description <../notebooks/data/mroz.des>`

Week 12
=======

*   :download:`Julia notebook for week 12 <../notebooks/students/week_12.ipynb>`