Aug. 07, 2019 »
The Battle Lines for 2020
» A new study finds that polarization on immigration may actually benefit Democrats
Jul. 30, 2019 »
Happy Debate Day! New Political Betting Markets
» The way I see it, the more prediction market data, the better
Jul. 27, 2019 »
A Note On Failure
» The sooner we give up on something doomed to failure or mediocrity the sooner we can move on to something better.
Mar. 22, 2019 »
R for Political Data Science Week 12: Do Voters Still Care About The Economy?
» It is unclear whether healthy economic conditions could help — or hurt — president Trump in 2020
Mar. 15, 2019 »
R for Political Data Science Week 11: Is Beto the Media Sweetheart?
» O’Rourke’s bid for the presidency has scored some big media attention
Mar. 08, 2019 »
R for Political Data Science Week 10: What If Each State Allocated Their Electoral College Votes Proportionally?
» A theoretically appealing idea, a proportional Electoral College would have a lot of room for error.
Mar. 01, 2019 »
R for Political Data Science Week 9: The “Strongest” Democrats and Republicans (That Ran for Office in 2018)
» Compared to their states’ partisanships, these popular Democrats did better/worse than expected
Feb. 22, 2019 »
R for Political Data Science Week 8: Four Parties in America? Probably Not Anytime Soon
» Voters are too partisan for America to have four parties.
Feb. 15, 2019 »
R for Political Data Science Week 7: The 2020 Twitter Primary
» Let’s mine Twitter data to check patterns of speech for differences between Democratic presidential candidates.
Feb. 08, 2019 »
R for Political Data Science Week 6: Just How Liberal Are the 2020 Democratic Candidates?
» Many 2020 hopefuls have signed on to the Green New Deal. What exactly does that mean, and how liberal are they?
Feb. 01, 2019 »
R for Political Data Science Week 5: The Ideological Diversity of the American Electorate
» What exactly are the voting preferences of the rumored “economically conservative, socially liberal” voter?
Jan. 25, 2019 »
R for Political Data Science Week 4: What Happens To Our Algorithms When Socialists Vote in Congress?
» Popular algorithms to calculate ideological scores for legislators might miss the meaning of counter-intuitive no votes.
Jan. 18, 2019 »
R for Political Data Science Week 3: How Marginal Tax Rates Work
» There has been some chatter about raising the top marginal tax rate to 70%. Here’s how tax rates actually work, and what a return to the 1970s rates could look like.
Jan. 11, 2019 »
R for Political Data Science Week 2: This Early Before 2020, It’s All About Name Recognition
» Ahead of the 2020 Democratic primary, there’s a very clear relationship between being better known and better liked.
Jan. 04, 2019 »
R for Political Data Science Week 1: Polarization in the 115th Congress
» How polarized were the most recennt members of the House of Representatives?
Dec. 23, 2018 »
The Best Books I Read in 2018
» In no particular order, these are the best books I read in 2018 (mostly about US politics) and a few words about each.
Nov. 26, 2018 »
Want to Know What Happened in the 2018 Midterms? Look at Rural America.
» Something has been bugging me about how we’re interpreting the midterms.
Nov. 06, 2018 »
The 2018 Midterms are Upon Us: Final Thoughts Beforehand
» Final forecasting thoughts and a preliminary dive into the data that will likely tell the story of this year’s midterms.
Oct. 10, 2018 »
LOESS vs Bayesian GAM for Finding Trends in Data
Sep. 29, 2018 »
Now Out: My Course “Analyzing Polling and Election Data in R” at DataCamp!
» Learn R for data science by wrangling, visualizing, and modeling political data like polls and election results