A Scalar Measure for Bias in (Multi-Party Pre-Election) Surveys

All surveys deviate from the true distributions of the variables, but some more so than others. This is particularly relevant in the context of election studies, where the true distribution of the vote is revealed on election night. Jocelyn Evans and I present a method for calculating a scalar measure that neatly summarises such bias for multi-party elections. We also present a Stata module that implements our new method.

Statistical Songs Roundup

Today is clearly a day for statistical songs (are there any other days?), so here are some links to get you started. To kick of the stat song roundup, here are some … interesting insights into the culture that is biostatics, complete with some remarkably dreadful audio material. Obviously, youtube has a whole channel devoted…

Random Fun Fact of the Day: Machine Learning and Statistics

Every sentient and internet enabled being in the Western world has by now noticed that Amazon’s “customers who bought this item” algorithm is one of the most successful exercises in machine learning. Like various algorithms used by Google, it is oftentimes accurate as well as slightly frightening.

A friend of mine (who is an engineer) told me that he bought an administrator’s guide to Cisco routers. Amazon concluded that he might also be interested in “Cooking for one”. I, on the other hand, recently browsed the excellent Cambridge “Dictionary of Statistics” and also had a look at “All of Statistics” (preposterous title, but an interesting book – incidentally, it tries to convey statistical basics to engineers interested in machine learning). Amazon suggested to round off my order with – drum roll – “Fifty Shades of Grey”. I’m sure my students would agree that there is an intimate link between these three titles.

Random Fun Fact of the Day: Machine Learning and Statistics 1

Running the Numbers

Via Simon Jackman’s blog: Chris Jordan found an intriguing way to visualise some very large, mostly scary national statistics, such as the as the number of plastic cups used on flights in the US every six hours (one million), or the number of cell phones retired every day (426,000). Amazing and aesthetically pleasing in a…

FAQ on Interaction

Six weeks ago, I have reviewed Kam’s and Franzese’s Modeling and Interpreting Interactive Hypotheses in Regression Analysis. This week, the topic of interaction effects pops up on the Social Science Statistics Blogs, with pointers to useful FAQs and other pages.Technorati Tags: interaction effects, statistics, regression

Review: Modeling and Interpreting Interactive Hypotheses in Regression Analysis

Many hypothesis in the social sciences involve interaction: The effect of some variable x (say xenophobia) on some variable y (say support for the extreme right) is conditional on a third variable z (say ethnicity). Modelling interactive hypotheses looks straightforward on the surface: simply generate a third variable by multiplying x and z and plug…