Wednesday, 30 June 2021

FlowingData

FlowingData


Still Flowing at 14

Posted: 30 Jun 2021 09:30 AM PDT

FlowingData turned 14 years old last week. Is that old? It feels old.

The site started as a sandbox to put class projects. Flat HTML files. JPEG files. Google Maps placemarkers. Flash. Vanilla JavaScript.

As I studied from across the country, it turned into a place to share links with classmates. Did you see that project on Infosthetics? How did Stamen make that map? These big infographics are getting out of hand.

I experimented. To my surprise and delight, stuff I made traversed the internets. Some work landed in my friends’ and family’s feeds through roundabout routes. I learned how visualization could reach a lot of people and get them excited about data.

Statistics grew out of that required course that everyone hated. Data also grew. It got big. It became a science.

Visualization grew with the data. Once thought of as just an analytical tool (to some), it developed into a medium for communication, expression, and storytelling.

As I finished my PhD, thinking about my future, I took job interviews. I think as the interviewee, you’re supposed to try to impress the interviewers. But deep down, it was the other way around for me. I was looking for someone to convince me that what they had to offer was better than running FlowingData. I didn’t find anything.

So, here I am, 6,243 posts, guides, tutorials, links, and projects later. Sheesh.

Thanks for reading. Thank you to supporting members. If you’re not a member yet and you’d like to keep the data flowing, I’d of course appreciate your support. I’m hoping to do this for many more years.

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Introduction to Modern Statistics

Posted: 30 Jun 2021 12:35 AM PDT

Introduction to Modern Statistics by Mine Cetinkaya-Rundel and Johanna Hardin is a free-to-download book:

Introduction to Modern Statistics is a re-imagining of a previous title, Introduction to Statistics with Randomization and Simulation book. The new book puts a heavy emphasis on exploratory data analysis (specifically exploring multivariate relationships using visualization, summarization, and descriptive models) and provides a thorough discussion of simulation-based inference using randomization and bootstrapping, followed by a presentation of the related Central Limit Theorem based approaches.

Read it in the browser or buy a print version. A good deal either way.

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