Editing Statistics and Statistical Programming (Winter 2021) (section)

===== Notes on finding a dataset =====

In order to complete your final project, you will each need a dataset. If you already have a dataset for the project you plan to conduct, great! If not, fear not! There are many datasets to draw from. Some ideas are below (please suggest others, provide updated links, or report problems). The teaching team will also be available to help you brainstorm/find resources if needed:

* Ask your advisor for a dataset they have collected and used in previous papers. Are there other variables you could use? Other relationships you could analyze?
* If there's an important study you loved, you can send a polite email to the author(s) asking if they are willing and able to share an archival or replication version of the dataset used in their paper. Be very polite and make it clear that this is starting as a class project, but that it might turn into a paper for publication. Make your timeline clear. In Communication and HCI, replication datasets are still very rare, so be prepared for a negative answer and/or questions about your motives in conducting the analysis.
* Do some Google Scholar and normal internet searching for datasets in your research area. You'll probably be surprised at what's available.
* Take a look at datasets available in the [https://dataverse.harvard.edu/ Harvard Dataverse] (a very large collection of social science research data) or one of the other members of the [http://dataverse.org/ Dataverse network].
* Look at the collection of social scientific datasets at [https://www.icpsr.umich.edu/icpsrweb/ICPSR/ ICPSR at the University of Michigan] (UW is a member). There are an enormous number of very rich datasets.
* Use the [http://scientificdata.isa-explorer.org/index.html ISA Explorer] to find datasets. Keep in mind the large majority of datasets it will search are drawn from the natural sciences.
* The City of Seattle has one of the best [https://data.seattle.gov/ data portal sites] of any municipality in the U.S. (and better than many federal agencies). There are also numerous administrative datasets released by other public entities (try searching!) that you might find inspiring.
* [http://fivethirtyeight.com FiveThirtyEight.com] has published a [https://cran.r-project.org/web/packages/fivethirtyeight/vignettes/fivethirtyeight.html GitHub repository and an R package] with pre-processed and cleaned versions of many of the datasets they use for articles published on their website.
* If you interested in studying online communities, there are some great resources for accessing data from Reddit, Wikipedia, and StackExchange. See [https://files.pushshift.io/reddit/ pushshift] for dumps of Reddit data, [https://meta.wikimedia.org/wiki/Research:Data here] for an overview of Wikipedia's data resources, and [https://data.stackexchange.com/ Stack Exchange's data portal].
* The NY Times is publishing a [https://github.com/nytimes/covid-19-data COVID-19 data repository] that includes county-level metrics for deaths, mask usage, and other pandemic-related data. The release a lot of it as frequently updated .csv files and the repository includes documentation of the measurements, data collection details, and more.
* The Community Data Science Collective and colleagues have created a [[COVID-19_Digital_Observatory| COVID-19 digital observatory]] (hosted in part right here on this wiki!) that publishes a bunch of pandemic-related data as csv and json files.
* The [https://openpolicing.stanford.edu Stanford Open Policing project] has published a huge archive of policing data related mostly to traffic stops in states and many cities of the U.S. We'll use at least one of these files for a problem set.