Daniel Kunin from Brown University created a totally stunning and interactive site named Seeing Theory. It provides a visual introduction to many concepts in statistics and probability. Definitely worth checking out and sharing with others.
Tip: it does not work well on mobile.
Data Visualization is not new. Check out this historical collection of 11 visualizations. Here are 2 big takeways for me.
- Even many many, years ago, data was being used to make decisions
- Visualizations have come a long way
Yes, this is an infographic of infographics.
Just this week, I have become aware of 3 free online books for data science.
- Interactive Charts
- Geographic Plots
Frontiers in Massive Datasets
Frontiers in Massive Datasets is a report all about how science, business, communications, national security and others need to learn to handle massive amounts of data. Whether the data has been sitting in a database for years or it is now just screaming into the systems, massive data is now a problem for almost every industry. This report covers many of the topics that need to be addressed when dealing with big data. Here is a very brief overview of the topics:
- Building Models from Massive Data
- Real-time Algorithms
- 7 Computational Giants of Massive Data Analysis
Foundations of Data Science
Foundations of Data Science is a draft of textbook written by John Hopcroft and Ravindran Kannan. It is intended to be a text for computer science with an emphasis more on probability and statistics rather than discrete mathematics. The authors argue that knowledge of working with data is a necessary skill for computer scientists of the future. This is clearly the most technical and academic of the 3 books, but if that is your thing, your should really enjoy browsing through this book. Here are some of the topics.
- High-Dimensional Space
- Algorithms for Massive Data Problems
- Singular Value Decomposition
- Graphical Models
Accel Partners, one of the largest big data investment firms, hosted a panel discussion on Data Visualization and Data Stories.
Hilary Mason, Data Scientist in Residence at Accel, hosts the discussion. Two great visualization experts that come up in the talk are, Fernanda Viégas and Martin Wattenberg.
There is nothing magical about this data. It is just income data. The magic comes from the excellent visualizations, and the story being told. If you need to make your data come to life, this video is an excellent example.
The blog post, Central Limit Theorem Visualized in D3, was posted last week.
I believe Christophe Viau put this list together. It is a very impressive list of D3.js examples. Each example includes the graph and the code to generate it.
D3.js Gallery Data – temporarily in view mode – Google Docs.
A more interactive and visual view of the examples can be found at this new, not yet complete, D3 Gallery.
This is a video infographic about pizza delivery in Manhattan. This is another good way to make data tell a story.
Not only is the topic interesting, but the concept of breaking the global population down into 100 people is brilliant. This infographic is easily understandable, and it conveys a whole lot of information in a clean and concise manner. For more about where the data came from, see the 100 People page.