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David McCandless: The beauty of data visualization

David McCandless: The beauty of data visualization
To create his infographic about nutritional supplements, it took McCandless a month to review about 1,000 medical studies and design the visual. Is that level of effort surprising, and do you think it’s worth it? Try out the interactive version that’s available on McCandless’s website. What engaged or surprised you? Related:  Business Analytics

Martin Seligman on positive psychology Seligman believes that there are three different types of happy lives: the pleasant life, the engaged life, and the meaningful life. Create an infographic explaining the three lives. The infographic should include a spokesperson who seems to represent each type of life; this could be someone you know, celebrity, a historical figure, or a character from TV, movies, or literature. Try what Seligman calls the “Gratitude Visit” [16:53]. Keep a written journal or a video diary to record your feelings before and after the exercise. Want to be happy? We all want to be happy. Hans Rosling - GapMinder Rosling is a passionate advocate for “liberating” publicly-funded data on the Internet. Select one topic area for which country-specific data might be compared (e.g., education, health, food production, the environment, etc.), and identify what you think are the best sources of data in this area on the Internet. Create a guide that lists these sources, and provides a brief review of each. If the administrators of these data repositories are thinking about how users might engage with the data via mobile devices or social media, note this in the review. Here are a few resources to make learning statistics an interesting experience. Someone always asks the math teacher, "Am I going to use calculus in real life?" The Institute for Statistics Education at is the leading provider of online education in statistics, and offers over 100 courses in introductory and advanced statistics.

Google Analytics 101: 3 Key Things You Can Learn Designing your new website, creating compelling content, and building out your social platforms is (sigh) the fun part. The sometimes not so fun—but just as important—part? Analytics! After all, if you don’t know how people are interacting with your brand, you won’t know how to make it better. So, where to begin? 1. Once you’ve installed Google Analytics on your website, you’ll have access to a Google Analytics dashboard. In addition to being really interesting, these stats can help you make business decisions moving forward. 2. Now that you know that (let’s say) 50,000 people are accessing your site each month, how long are those 50,000 visitors staying? Remember: The longer, the better! Next, taking a look at “New vs. Once you start tracking this metric, make a note of when it goes up or down. 3. Google Analytics offers an extremely valuable analytic called “Traffic Sources,” which explains how your visitors ended up on your site.

Kevin Slavin: How algorithms shape our world Slavin worries about our reliance on algorithms: “We’re writing these things that we can no longer read. And we’ve rendered something illegible, and we’ve lost the sense of what’s actually happening in this world that we’ve made.” What’s more, Slavin believes we may not even realize it, as the algorithms “acquire the sensibility of truth because they repeat over and over again, and they ossify and calcify, and they become real.” Imagine Slavin’s examples taken two or three steps further, and create a short story set in a world that is completely dominated by computer algorithms. MoveOn’s former executive director and online activist Eli Pariser took the TED stage in 2011 to warn about the unintended consequences of algorithms that personalize people’s online experiences. Watch his talk, “Beware online filter bubbles."

Breathingearth - Births / Deaths live data feed Addressing the Analytics Skills Gap On the final day of last week's MIT Symposium, the sole focus was on the skills gaps organizations are facing in trying to advance their analytics efforts – and what corporations and universities are doing about it. A great many companies are looking to hire talent for their analytics teams – but that talent is in short supply. Try searching for analytics jobs on any of the popular job boards. We are seeing the skills crunch within HR organizations. One of the biggest skills gaps on these teams today is the ability to tell the story – someone who can take data or a statistical model and explain it to business leaders in terms of what it means, why they should care, and what they should do about it. In the meantime, what are HR leaders doing to bridge the skills gap within their organizations? Figure 1.

Ed | Clay Shirky: How Social Media can Make History Shirky says that before the Internet and social media, over the past 500 years, there were only four periods where media changed enough to warrant the label “revolution.” Research these revolutions and create a visual way to represent their key features. Do you have a guess about what the next revolution might bring? If so, add it in! As social media enables citizen reporting and greater interaction between news organizations and their audiences, the boundaries of journalism and ideas about what constitutes news are changing. Explore this phenomenon by conducting a survey about people’s attitudes and behaviors related to news and journalism. TED: Paul Lewis: Crowdsourcing the news Online Journalism Review: “The pros and cons of newspapers partnering with ‘citizen journalism’ networks” Foreign Affairs, From Innovation to revolution: Does social media make protests possible?

What to Ask Your "Numbers People" - Tom Davenport by Tom Davenport | 9:00 AM July 12, 2013 If you’re a manager working with the analysts in your organization to make more data-driven business decisions, asking good questions should be one of your top priorities. Many managers fear that asking questions will make them appear unintelligent about quantitative matters. However, if you ask the right kinds of questions, you can both appear knowledgeable and advance the likelihood of a good decision outcome. In my new book (co-authored with Jinho Kim) Keeping Up with the Quants, and in a related article in this month’s HBR, we list a lot of possible questions for various stages of analysis. But in this short article, I thought it might be useful not only to mention a couple of the most important questions you can ask about data, but what some of the ensuing dialogue might involve. 1.Questions about Assumptions You ask: What are the assumptions behind the model you built? 2. You ask: How are the data you gathered distributed? You get the picture.

Kevin Alloca: Why videos go viral Allocca asks, “Who could have predicted any of this?” It’s amazing to “rewind” from the way we currently experience moving images (video) to consider the first motion pictures, produced a little over a hundred years ago. Research the history of moving images. What advances in technology have changed the way people engage with film and video? What do you think will happen over the next hundred years? What is big data? - Bringing big data to the enterprise TDWI Big Data Maturity Model and Assessment Tool Sponsored by IBM, this big data maturity online assessment tool enables organizations to objectively measure the maturity of an enterprise’s big data analytics program across five dimensions that are key to deriving value from big data analytics: organization, infrastructure, data management, analytics, and governance. Take it today! Big Data Hadoop Solutions, Q1 2014 Descritption: Read the report to see why IBM InfoSphere BigInsights was named a leader and how it stands in relation to other big data Hadoop vendors. Read the report The top five ways to get started with big data Learn how to determine which of the five can be your first step into big data. Get the white paper The FOUR V’s of Big Data IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. View the infographic Understanding big data Gain insight into IBM’s unique in-motion and at-rest big data analytics platform. Get the ebook Get the eBook

Re-thinking Progress: The Circular Economy The circular economy is a generic term for an industrial economy that is, by design or intention, restorative and in which materials flows are of two types, biological nutrients, designed to reenter the biosphere safely, and technical nutrients, which are designed to circulate at high quality without entering the biosphere. The term encompasses more than the production and consumption of goods and services, including a shift from fossil fuels to the use of renewable energy, and the role of diversity as a characteristic of resilient and productive systems. It includes discussion of the role of money and finance as part of the wider debate, and some of its pioneers have called for a revamp of economic performance measurement tools The circular economy is grounded in the study of feedback rich (non-linear) systems, particularly living systems. A major outcome of this is the notion of optimising systems rather than components, or the notion of ‘design for fit’.