Data visualization

And the winner is...

The midterm project for my data visualization course this past fall required students to submit to the ASA’s Police Data Challenge. The competition involved analyzing millions of 911 calls for one of three cities (Baltimore, Cincinnati, or Seattle). I had the students investigate the Seattle data set, since it contained latitudes and longitudes of each call. Several weeks later, we received the exciting news that one of the teams won “Best Overall” among undergraduate teams!

Quantifying thrill

Monday morning, October 30, found me groggy and sandy-eyed. The culprit was the 5-hour and 17-minute, 10-inning thriller between the LA Dodgers and Houston Astros in Game 5 of the 2017 the night before. Thanks to living in the Central Time Zone, I went to bed around 1am. The Astros ended up defeating the Dodgers 13-12, but the game was insane, featuring three comebacks from deficits of 3 runs or more.

Racial disparity in Winona Area Public School District

This visualization project was inspired by the excellent This American Life episode, Is This Working? The entire episode is well worth a listen, but the gist of the episode was that racial inequity in disciplinary action translates into racial inequity in academic outcomes. I was curious to see if this association held up, in the Winona Area Public Schools, using publicly available data from the Minnesota Department of Education Data Center.

#OscarsSoWhite

As I was watching Chris Rock host the 2016 Oscars, I decided to finally scratch my curiosity itch and learn R’s Twitter API, twitteR. The 2016 Oscars were controversial, due to the fact that all the actors and actresses nominated were white for the second year in a row. Chris Rock made sure to point this out in his opening monologue, and tweets began using the hashtag #OscarsSoWhite to advance the conversation.