Category Archives: Recommended

Recommended: Philosophy News Network: Postmodernism Special Report

I generally shy away from Philosophical debates, but I did discuss a Postmodern critique of Evidence Based Medicine a while back. When one of my more intellectual friends posted a link to a commentary on Postmodernism on the Existential Comics web site, I had to take a look. I think I did a pretty good job of summarizing Postmodernism without stereotyping it, but maybe I’m setting my standards too low if I try to compete with a comic strip. You can judge for yourself. Continue reading

Recommended: The Origins of ‘Big Data’

I’m not a big fan of the term “big data” but I’ve been applying for a couple of jobs that ask for expertise in big data instead of expertise in Statistics. So in one of the cover letters, I wrote that I was doing big data analysis before the term was even coined. That forced me to do a quick fact check, and it looks like the term first came into wide use in the late 1990s. Here’s an article on the person who first coined the term “big data.” Continue reading

Recommended: Designing and conducting semi-structured interviews for research

This is a very helpful guide on collecting qualitative data through a semi-structured interview. It emphasizes the need for probe questions and on behaviors that you should adopt to put your subject at ease and get the best information possible. This handout was developed for a college course on Organizational Communication, and the syllabus for this class has other valuable resources. Continue reading

Recommended: Network analysis in cross-sectional data using R

These are the slides for a very nice webinar presented by Eiko Fried. Dr. Fried provided a wealth of resources during his webinar (some of these are behind pay walls).

He offered examples of network analysis in the study of bereavement and depression and of post-traumatic stress disorder. He also provided tutorial papers on network models with binary data and regularized partial correlation networks., as well as a nice general overview of network models in mental health. He shared a blog posting on the relationship between a latent variable model and a network model and a facebook page on psychological dynamics. He also showed analyses from several R packages, qgraph, IsingFit, and bootnet. I’m putting those links here so I don’t lose track of them when I revisit this stuff six months from now.

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Recommended: Can A.I. be taught to explain itself

This is a nice article in the popular press that talks about some of the problems with “black box” models (in particular deep neural nets) used extensively in many big data projects. It is a bit shy on technical details, which is understandable for a paper like the New York Times. Even so, the stories are quite intriguing. This is a wake up call for those people who fail to recognize the serious problems with many big data models. Continue reading

Recommended: beanumber repository

This is the github repository of Ben Baumer. He is one of the co-authors of “Modern Data Science with R” and the data and code from that book is available here. He also provides code and data for OpenWAR, an open source method for calculating a baseball statistic, Wins Above Replacement. Finally, there is an R library for extracting, transforming, and loading “medium” sized datasets into SQL. Medium here means multi-gigabyte sized files. Related to this are a couple of “medium” sized data sets from the Internet Movie Database and from the NYC CitiBike dataset. Continue reading