Given the recent votes on same-sex marriage in New Jersey and Portugal, I wanted to test a seemingly innocuous claim that touches upon very broad issues in political theory: does the degree of directness of a “democratic” vote predict whether the vote will promote or prohibit same-sex marriage? Naively, it seemed clear to me that
Posts Tagged ‘ statistics ’
Typos in Chapter 4
Chapter 4 of “Introducing Monte Carlo Methods with R” has four typos (so far) in the exercises:
– In Exercise 4.5, the should not be in bold fonts (!)
– In Exercise 4.9, I commented too many lines when revising and thus the variance terms vanished. It should read
– In Exercise 4.13, following the removal of 
sequential ideal point estimates
Out of curiosity, I produced a “sequential” set of ideal point estimate for the (current) 111th U.S. Senate, plotting the results in the graph attached below (click on the thumbnail); as is conventional, red is Republican and blue is Democratic. The analysis uses all 373 non-unanimous roll calls in the 111th Senate thus far. Each
Killing Yourself: An Addendum
In further support of the claim that a lot of deaths are partly self-induced, here’s a fascinating piece by Wired on the extraordinary rise in the percent of deaths among the young caused by their own poor decisions. It’s remarkable that, for the young, modern science has already made the world so safe that humanity,
R Tutorial Series: ANOVA Tables
The commonly applied analysis of variance procedure, or ANOVA, is a breeze to conduct in R. This tutorial will explore how R can be used to perform ANOVA to analyze a single regression model and to compare multiple models.Tutorial FilesBefore we begin,...
Samples per series/dataset in the NCBI GEO database
Andrew asks: I want to get an NCBI GEO report showing the number of samples per series or data set. Short of downloading all of GEO, anyone know how to do this? Is there a table of just metadata hidden somewhere? At work, we joke that GEO is the only database where data goes in, 
Typos in Chapter 3
Here are two more typos in the exercises of Chapter 3 of “Introducing Monte Carlo Methods with R”.
– due to the (later) inclusion of an extra-exercise in the book, the “above exercise” in Exercise 3.5 actually means Exercise 3.3.
– in Exercise 3.11, question c, a line got commented by mistake in the LaTeX file and 
Typos in Chapter 2
When grading homeworks for my Monte Carlo graduate class, I found that my students had pointed out two typos in the exercises of Chapter 2 of “Introducing Monte Carlo Methods with R”.
– In Exercise 2.17, question d. should be “d. Show that the maximum of is attained at .“
– In Exercise 2.21, in item 
Announcing r-ORM: A Pure R Object-Relational Mapper
My apologies for the long break between posts. Before the end of this week I’ll return to my series of posts on image processing in R. In the intervening time, I’ve finished a piece of code that I’d like to officially release to the public. The code in question is a very minimal object-relational mapper
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
