Teaching and resources

Data wrangling in R

• I put together a short explanation of some common data wrangling tasks in R for my students. You can find it here.

Class materials

I teach two classes here at the KDI School for which I have made my materials publicly available. In both cases:

• The raw quarto/markdown files for the slides contain plenty of useful comments and examples.
• All of the data I use as examples in class are uploaded to the repository so you can follow along and do the examples yourself.
• Please feel free to make use of any of the code. Or, if you have questions, feel free to e-mail me!
  • If you find something of interest in the HTML slides, then definitely check out the .qmd files. There are examples of animating graphs, creating maps, and much more.

Applied microeconometrics in R

I teach an advanced masters/Ph.D. class on applied microeconometrics in R. The resources are available on my Github page, here.

• Note that I have transitioned to Quarto and HTML slides, but the older markdown files are available in the weeks folder.

Geospatial data analysis in R

I teach a masters class on geospatial data analysis in R. The resources are available on my Github page, here.

• All slides are HTML and made using Quarto (in R).

Working with others

I put together some slides for our Ph.D. students focused on setting up projects when working with others. These slides focus on two things:

1. Using Dropbox to keep all files up to date
2. Using relative paths so that files run on everyone’s computer

You can view the slides here.

Geospatial data and small area estimation

Stay tuned for a primer aimed at discussing the ins and outs of integrating geospatial data and survey data for small area estimation in R, with a particular emphasis on improving estimates of SDGs.

• This work is with UN Stats and is aimed at practitioners and national statistics offices, but it will also contain a short guide on using geospatial data.
• In the meantime, please check out UN Stats’ SAE4SDG page, here.
• As part of this work, I taught a workshop in Nairobi and one in Bangkok, in combination with UN Stats, UNECA, UNEAC, and UNESCAP on integrating geospatial data into small area estimation. Much of this draws from my geospatial class above, but you can also find the slides for the Bangkok workshop on the UNESCAP GitHub page, here.
• There are also two upcoming R packages that will make this easier. Please check back for updates!
  • povmap
  • geolink