## Learning LaTex

This document serves as an introduction to LaTeX. It is meant for someone starting from scratch and covers installation and basic operations using the program. The pdf file will start you off, and the .tex file is the LaTeX code used to produce the pdf.

latex_introduction_first_workshop_1_26.pdf

latex_introduction_first_workshop_1_26.tex

latex_introduction_first_workshop_1_26.pdf

****latex_introduction_first_workshop_1_26.tex

**Introduction to instrumental variable regression**

This document is a brief introduction to instrumental variable regression. It covers "endogeneity" which is caused by omitted variables, measurement error, and simultaneity and explains what kinds of problems this introduces to statistical analyses. It covers two-stage least squares, choosing instruments, and post-estimation tests.

**ivregression.pdf**## Cowcodes

Merging datasets is often problematic for political scientists as we need a unique country-year identifier that matches in two datasets. This file is used in STATA to recode a `country' variable into a cowcode. It includes many different country spellings and has been updated for years. I did not create this myself (I believe the original was created by Jana von Stein and I received an updated version from Dave H. Clark.

cowcodes.do

cowcodes.do

## Introduction to R

The R programming language is very useful for statistical analysis. The attached zip file contains a folder with slides, datasets, and R code to help learn the R language, it also includes assignments for each lecture which allow you to try out the code yourself.

This was put together when I was in graduate school (lots of spelling errors) and meant covered an intro to data science as well. I have deleted as much of the information on data science theories and considerations as I could manage so that it provides mostly code for using R. The R scripts contain a lot of detail on what each part of the code does, and the slides help visualize the output and explain what we are doing.

introduction_to_r.zip

This was put together when I was in graduate school (lots of spelling errors) and meant covered an intro to data science as well. I have deleted as much of the information on data science theories and considerations as I could manage so that it provides mostly code for using R. The R scripts contain a lot of detail on what each part of the code does, and the slides help visualize the output and explain what we are doing.

introduction_to_r.zip