cshalizi + to_teach:statcomp + kith_and_kin   4

Interactive R On-Line
"IROL was developed by the team of Howard Seltman (email feedback), Rebecca Nugent, Sam Ventura, Ryan Tibshirani, and Chris Genovese at the Department of Statistics at Carnegie Mellon University."

--- I mark this as "to_teach:statcomp", but of course the point is to have people go through this _before_ that course, so the class can cover more interesting stuff.
R  kith_and_kin  seltman.howard  nugent.rebecca  genovese.christopher  ventura.samuel  tibshirani.ryan  to_teach:statcomp 
august 2016 by cshalizi
Red State/Blue State Divisions in the 2012 Presidential Election
"The so-called “red/blue paradox” is that rich individuals are more likely to vote Republican but rich states are more likely to support the Democrats. Previ- ous research argued that this seeming paradox could be explained by comparing rich and poor voters within each state – the difference in the Republican vote share between rich and poor voters was much larger in low-income, con- servative, middle-American states like Mississippi than in high-income, liberal, coastal states like Connecticut. We use exit poll and other survey data to assess whether this was still the case for the 2012 Presidential election. Based on this preliminary analysis, we find that, while the red/ blue paradox is still strong, the explanation offered by Gel- man et al. no longer appears to hold. We explore several empirical patterns from this election and suggest possible avenues for resolving the questions posed by the new data."
to:NB  have_read  us_politics  statistics  to_teach:undergrad-ADA  to_teach:statcomp  kith_and_kin  gelman.andrew 
july 2013 by cshalizi
My Stat Bytes talk, with slides and code | Nathan VanHoudnos
"I will present a grab bag of tricks to speed up your R code. Topics will include: installing an optimized BLAS, how to profile your R code to find which parts are slow, replacing slow code with inline C/C++, and running code in parallel on multiple cores. My running example will be fitting a 2PL IRT model with a hand coded MCMC sampler. The idea is to start with naive, pedagogically clear code and end up with fast, production quality code."
kith_and_kin  computational_statistics  R  vanhoudnos.nathan  to_teach:statcomp 
june 2013 by cshalizi

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