About that claim in the NYT that the immigration issue helped Hillary Clinton? The numbers don’t seem to add up.

Today I noticed an op-ed by two political scientists, Howard Lavine and Wendy Rahm, entitled, “What if Trump’s Nativism Actually Hurts Him?” … Now I was curious, so I thought I’d check the numbers. CONT. Andrew Gelman (Columbia U.), Statistical Modeling, Causal Inference, and Social Science Read more »

Two Ways of Thinking About Election Predictions and What They Tell Us About 2018

To understand the differences between quantitative, data-driven predictions and those made from traditional, data-influenced handicapping, one should direct their attention to the names of two websites: Sabato’s Crystal Ball at the University of Virginia Center for Politics, and my blog, The Crosstab. One is a reference to the soothsayer, a […] Read more »

How surprising was Trump’s victory? Evaluations of the 2016 U.S. presidential election and a new poll aggregation model

The U.S. presidential election results of 2016 surprised many poll-watchers, suggesting possible biases in estimated support for the major party candidates and posing a challenge for poll aggregation as a prediction tool. Using data from earlier elections and the 2016 campaign, we evaluated poll aggregation performance for the major prediction […] Read more »

Book Review: ‘News, Numbers and Public Opinion in a Data-Driven World’

In 1954, Darrell Huff published How to Lie with Statistics, a tongue-in-cheek guide for those wanting to use numbers to deceive. The book, now widely distributed to first-year university statistics students, outlines how statistics can confuse and muddle both writers and readers. The upshot? Huff suggests that: ‘without writers who […] Read more »