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Links 1 through 10 of 59 by Ramit Sethi tagged data

Great insight -- "In the latest edition of Stocks For the Long Run, Jeremy Siegel offered up a great stat on the small cap premium. From 1926-2012, small cap stocks returned 11.5% per year while the large cap S&P 500 returned 9.7%. But if you were to exclude the 1975-1983 period, which coincides with ERISA laws that made it easier for pensions to diversify into small caps, the annual returns for both large and small caps would be almost identical at around 8% per year."

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Fascinating how Netflix took Pandora-like approach to tagging movies, but went much deeper

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Many people who are injured in a fight never reported it to police, it turned out. That was particularly true with fights happening inside pubs and clubs. "They don't know who the perpetrator was, so what's the point of going to the police?" Shepherd tells Shots. "And they're afraid of having their own conduct scrutinized. If it's a fist fight or gang related or drug related, nobody's going to want to go to the police." So the hospital started sharing its information with the police, after removing names and other identifying information. With that anonymous information, authorities found they could do a much better job of targeting violence hot spots. That and other measures reduced the social and economic costs of violence in Cardiff by about $11 million in 2007, according to the study, which was published in the journal Injury Prevention.

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For the first time, a massive data set of 10,000 porn stars has been extracted from the world’s largest database of adult films and performers. I’ve spent the last six months analyzing it to discover the truth about what the average performer looks like, what they do on film, and how their role has evolved over the last forty years.

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For at least a year, Netflix has been explicit about its plans to exploit its Big Data capabilities to influence its programming choices. “House of Cards” is one of the first major test cases of this Big Data-driven creative strategy. For almost a year, Netflix executives have told us that their detailed knowledge of Netflix subscriber viewing preferences clinched their decision to license a remake of the popular and critically well regarded 1990 BBC miniseries. Netflix’s data indicated that the same subscribers who loved the original BBC production also gobbled down movies starring Kevin Spacey or directed by David Fincher. Therefore, concluded Netflix executives, a remake of the BBC drama with Spacey and Fincher attached was a no-brainer, to the point that the company committed $100 million for two 13-episode seasons.

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Really good presentation on the only 3 metrics to care about. Includes sample charts/spreadsheets for dashboard, funnel analysis, cohort analysis.

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Cool-looking site lets you track a ton of data, manipulate/graph it. For example, # of calories eaten, bike miles ridden, etc. Not sure what I'd use this for, though

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Cool visualization guide shows you which chart to use, depending on what you're trying to show and how much data you have

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I was recently privy to a product prioritization meeting in a relatively large company. It was fascinating. The team spent an hour trying to decide on a new pricing strategy for their main product line. One of the divisions, responsible for the company’s large accounts, was requesting data about a recent experiment that had been conducted by another division. They were upset because this other team had changed the prices for small accounts to make the product more affordable. Almost the entire meeting was taken up with interpreting data. The problem was that nobody could quite agree what the data meant. Many custom reports had been created for this meeting, and the data warehouse team was in the meeting, too. The more they were asked to explain the details of each row on the spreadsheet, the more evident it became that nobody understood how those numbers had been derived.

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