As a celebration of Florence Henderson’s 79th birthday (on February 14), I have created this scatterplot to use in my regression course. The plot depicts the relationship between time spent on mathematics homework outside of school (expressed as z-scores) and … Continue reading →
Inspired by Preis et al.’s article Quantifying the advantage of looking forward, recently published in Scientific Reports (one of Nature publishing group’s journals), I wondered if similar big-data web-based research methods might address a question even bigger than how much different countries wonder about next year. How about the meaning of life. Who is searching
In the past, I wrote about robust regression. This is an important tool which handles outliers in the data. Roger Koenker is a substantial contributor in this area. His website is full of useful information and code so visit when … Continue reading →
This is the second of a two part reexamination of Florence Nightingale's data visualization based on her innovative cam diagrams (my term) shown in Figure 1.
Figure 1. Nightingale's original cam diagrams (click to enlarge)
We just released Stan 1.1.1 and RStan 1.1.1 As usual, you can find download and install instructions at: http://mc-stan.org/ This is a patch release and is fully backward compatible with Stan and RStan 1.1.0. The main thing you should notice is that the multivariate models should be much faster and all the bugs reported for
Collinearity, or excessive correlation among explanatory variables, can complicate or prevent the identification of an optimal set of explanatory variables for a statistical model. For example, forward or backward selection of variables could produce inconsistent results, variance partitioning analyses may be unable to identify unique sources of variation, or parameter estimates may include substantial amounts 
(see John Wilkins’ article on the – interesting – history of that phrase http://scienceblogs.com/evolvingthoughts/…). We will see, this week in class, several smoothing techniques, for insurance ratemaking. As a starting point, assume that we do not want to use segmentation techniques: everyone will pay exactly the same price. no segmentation of the premium And that price should be related to...
A couple of weeks ago, I posted about how much we can expect to learn about the state of the world on the basis of a statistical significance test. One way of framing this question is: if we’re trying to come to scientific conclusions on the basis of statistical results, how much can we update 
Let's get back to the age-value relationship from my last post. I did some more plotting to see on which position this inversed U-shaped relationship is strongest. Please note, that I use a dataframe called eu.players throughout this post, which holds ...
Following the roundabout tour of F1Stats – A Prequel to Getting Started With Rank Correlations, here’s a walk through of my attempt to replicate the first part of A Tale of Two 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
