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
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
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
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.
This is a short overview of five major social media sites: LinkedIn, Twitter, Facebook, Instagram, and Snapchat and how you might use them to promote your career. The article ends with a few good overall suggestions. Continue reading
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
This is a page outlining several related efforts at RStudio to make it seaier for you to work with data stored in various relational databases. Continue reading
This is a series of videos and homework exercises that you can work on at your own pace. I have only viewed the outline for this, but anything from DataCamp comes highly recommended. Continue reading
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
This paper talks about how to get students to think about large databases in an introductory class that normally uses “toy” problems with a few dozen rows of data. Continue reading