Untitled. Data is beautiful, data is a story. Packages. Using R to quickly create an interactive online map using the leafletR package. The Molecular Ecologist. First off, thanks to Tim and Jeremy for the invitation to write a guest post here on using R to make maps!
As a brief introduction, my name is Kim Gilbert, and I am a Ph.D. student at the University of British Columbia working with Mike Whitlock. I am broadly interested in population genetics and population structure, and am currently studying local adaptation in a tree species. If you want to know more, check out my website, where I also have this tutorial as a .pdf presentation. Okay, onward with R! And apologies in advance that the R code provided will not show color coded text (a limitation of wordpress), but I decided that it is more useful to leave as text in order to allow copying and pasting rather than insert screenshots that might look nicer but require retyping on your part.
Packages. Data Science - Community. Web Technologies and Services. Data Sets. Index of /ml/machine-learning-databases. Publishable Stuff. DataRemixed. VizWiz - Data Visualization Done Right. Visual Business Intelligence. This is my response to a recent blog article by Robert Kosara of Tableau Software titled “3D Bar Charts Considered Not that Harmful.”
Kosara has worked in the field of data visualization as a college professor and a researcher for many years, first at the University of North Carolina and for the last several years at Tableau. He’s not a fly-by-night blogger. But even the advice of genuine experts must be scrutinized, for gaps in their experience and biases, such as loyalties to their employers, can render their advice unreliable. It has become a favorite tactic of information visualization (infovis) researchers to seek notoriety by discrediting long-held beliefs about data visualization that have been derived from the work of respected pioneers.
For example, poking holes in Edward Tufte’s work in particular now qualifies as a competitive sport. Back to Kosara’s recent blog article. We should certainly encourage people to use charts in ways that lead them to think and ask questions. VC blog. Posted: February 19th, 2014 | Author: Manuel Lima | Filed under: Uncategorized | No Comments » As many readers might have noticed, from my first and most recent book, I’m slightly obsessed with medieval information design, and the remarkable work of many our visualization forefathers, such as Isidore of Seville (ca. 560–636), Lambert of Saint-Omer (ca. 1061–ca. 1125), or Joachim of Fiore (ca. 1135–1202).
Information aesthetics - Data Visualization & Information Design. Principal Component Analysis step by step. In this article I want to explain how a Principal Component Analysis (PCA) works by implementing it in Python step by step.
A Quick-R Companion. R for Public Health. DiffusePrioR. Blog. An introductory comparison of using the two languages.
Background R was made especially for data analysis and graphics. SQL was made especially for databases. They are allies. Error Statistics Philosophy. Machine Learning (Theory) Data Mining: Text Mining, Visualization and Social Media. The Turing Test for artificial intelligence is a reasonably well understood idea: if, through a written form of communication, a machine can convince a human that it too is a human, then it passes the test.
The elegance of this approach (which I believe is its primary attraction) is that it avoids any troublesome definition of intelligence and appeals to an innate ability in humans to detect entities which are not 'one of us'. This form of AI is the one that is generally presented in entertainment (films, novels, etc.). However, to an engineer, there are some problems with this as the accepted popular idea of artificial intelligence. I believe that software engineering can be evaluated in a simple measure of productivity. Hilarymason.com. Big Data, Plainly Spoken (aka Numbers Rule Your World) Two years ago, Wired breathlessly extolled the virtues of A/B testing (link).
A lot of Web companies are in the forefront of running hundreds or thousands of tests daily. The reality is that most A/B tests fail. A/B tests fail for many reasons. Typically, business leaders consider a test to have failed when the analysis fails to support their hypothesis. "We ran all these tests varying the color of the buttons, and nothing significant ever surfaced, and it was all a waste of time! " Bad outcome isn't the primary reason for A/B test failure. 1. 2. 3. These issues are often ignored or dismissed. The Facebook Data Science team just launched an open platform for running online experiments, called PlanOut. The rest of this post gets into some technical, sausage-factory stuff, so be warned.
Statisfaction. Statisfaction. Doing Bayesian Data Analysis. Three-Toed Sloth. "Learning Spatio-Temporal Dynamics" : Boasting about my student's just-completed doctoral dissertation. Over 2500 words extolling new statistical methods, plus mathematical symbols and ugly computer graphics, without any actual mathematical content, or even enough detail to let others in the field judge the results.
On Monday, my student Georg M. Blog. Old tails: a crude power law fit on ebook sales We use R to take a very brief look at the distribution of e-book sales on Amazon.com.
Read more… You don’t need to understand pointers to program using R Practical Data Science with R: Release date announced It took a little longer than we’d hoped, but we did it! If you haven’t yet, order it now! Access to Statistics. An Academic Blogging Experiment. Bayesianbiologist.