Knowledge Visualization Credit Scoring, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook "Thank you and thank you again for providing a complete, well-structured, and easy-to-understand online resource. Every other website or snobbish research paper has not deigned to explain things in words consisting of less than four syllables. I was tossed to and fro like a man holding on to a frail plank that he calls his determination until I came across your electronic textbook...You have cleared the air for me. You have enlightened. — Mr. "As a professional medical statistician of some 40 years standing, I can unreservedly recommend this textbook as a resource for self-education, teaching and on-the-fly illustration of specific statistical methodology in one-to-one statistical consulting. — Mr. "Excellent book. — Dr. "Just wanted to congratulate whoever wrote the 'Experimental Design' page. — James A. Read More Testimonials >> StatSoft has freely provided the Electronic Statistics Textbook as a public service since 1995. Proper citation: (Electronic Version): StatSoft, Inc. (2013).
Scary Big Data, Cool 3D Analytics and More What’s going on in the analytics world this week? Big, Scary Big Data The New York Times did some “etymological detective work” to resolve the tricky question of who first coined the term “big data” in its current meaning (and some man-in-the street reporting shows that nobody really knows what they current meaning is). What we do know is that big data is powerful, and that means it’s also potentially scary. In the future, your credit rating might be determined by what you post on social networks. Not scared yet? The flip side of scary data is data that can save lives. 3D Meets Analytics 3D imaging meets dashboards with SAP Visual Enterprise: Gaming company Bigpoint use HANA to ensure Battlestar Galactica Online players stay in the game even after their ship has just been blown up: SAP HANA Is Music to Execs’ Ears (and Startups) SAP is helping disrupt business: here’s a nice balanced piece by ASUG about John Deere’s choice of SAP Business Suite powered by SAP HANA. Mobile, Social, and Cloud
Naval Postgraduate School - Library All classes meet in room 151. HELP! I cannot get into my favorite journal or database Sorry – it is a new calendar year. Due to contracting problems and the delayed federal budget, we are experiencing some database and eJournal service interruptions. If you are denied access to any of our electronic resources, you may ask for help at the General Information or Ask a Librarian desk, or place an Interlibrary Loan request and we will quickly borrow the article/book you need during this unfortunate interruption to our service. Thanks for your patience, we are working hard to restore access. New Research Guides and Articles & Research Databases Page The December 2013 NPS theses are now available!
Free Open source Geocoder via REST webservices (for geonames and openstreetmap data) Propositional density in visualization A couple of months ago, I came across a very insightful article with high relevance for information visualization: “More with less” in the always excellent ACM interactions. It made me think quite a bit, and might also help some to understand a designer’s approach to visualization a bit better, so here is the gist of the story (the following section mostly paraphrases the original article). Propositional density Let us start with the notion of a proposition: in this context, a proposition is simply an elementary, atomic statement about the object at hand. “The FedEx logotype is purple” and “The FedEx logotype is set in a sans-serif font” are propositions, and because they describe salient, perceptible properties of the design, they are referred to as surface propositions. Now, the FedEx logo became famous for a perceptual trick: The white space between the E and the x creates an arrow. Now we have all elements together to define propositional density more precisely: Example: High altitude
A second draft of a non-technical article on universality I’ve spent the last week or so reworking the first draft of my universality article for Mathematics Awareness Month, in view of the useful comments and feedback received on that draft here on this blog, as well as elsewhere. In fact, I ended up rewriting the article from scratch, and expanding it substantially, in order to focus on a more engaging and less technical narrative. I found that I had to use a substantially different mindset than the one I am used to having for technical expository writing; indeed, the exercise reminded me more of my high school English assignments than of my professional work. (This is perhaps a bad sign: English was not exactly my strongest subject as a student.) The piece now has title: “E pluribus unum: from complexity, universality”. By coincidence, I moved up and expanded the other US-centric item – the discussion of the 2008 US presidential elections – to the front of the paper to play the role of the hook. 1. Do I contradict myself? Fig 2. Fig 3. 2.
Graph Visualization and Neo4j So far we’ve learned how to get Neo4j up and running with Neography, how to find friends of friends and degrees of separation with the Neo4j REST API and a little bit of the Gremlin and Cypher languages. However, all we’ve seen is text output. We haven’t really “seen” a graph yet, but that’s about to change. Vouched holds a graph of skill specific recommendations people have made to each other and visualizes it. I extracted the visualization, and hosted it on github as neovigator. You can get your very own visualization up and running or take a look at this instance running on Heroku. Let’s get it up and running and then we’ll go through some pieces of the code. Then visit localhost:9292 to see it running. The website is a Sinatra Application with only two routes. The JSON object we create will have this structure: When we fill this JSON object and pass it to the visualization, this is what we get: We create a route in Sinatra and set it to return JSON. Update! Like this: Like Loading...
US Federal Contract Spending Data Visualization :: Pitch Interactive, Inc. This is our original work A sans-circle version An additional iteration that helps address the overlap and transparency between the connections and labels. What our government spends vs. how much we talk about it. For the right visualization, we used the New York Times API to parse through all articles written in 2009. You can find detailed federal spending data on this page and the results of the NYT API call we made. Thanks to Political Math ( for bringing our attention to an initial assumption we made that was incorrect. Below is an iteration made by Political Math that shows the TOTAL amount of federal spending. Our focus here was on exploring new ways to visualize government data. What's the problem with contract spending? That said, the work we did is still valid for the point we want to make. As with the process of all other visualizations we do, our process was evolutionary. Now, how we went about creating this piece: US Federal Contract Spending