andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-402 knowledge-graph by maker-knowledge-mining
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Introduction: Anthony Goldbloom writes: For those who haven’t come across Kaggle, we are a new platform for data prediction competitions. Companies and researchers put up a dataset and a problem and data scientists compete to produce the best solutions. We’ve just launched a new initiative called Kaggle in Class, allowing instructors to host competitions for their students. Competitions are a neat way to engage students, giving them the opportunity to put into practice what they learn. The platform offers live leaderboards, so students get instant feedback on the accuracy of their work. And since competitions are judged on objective criteria (predictions are compared with outcomes), the platform offers unique assessment opportunities. The first Kaggle in Class competition is being hosted by Stanford University’s Stats 202 class and requires students to predict the price of different wines based on vintage, country, ratings and other information. Those interested in hosting a competition f
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1 Anthony Goldbloom writes: For those who haven’t come across Kaggle, we are a new platform for data prediction competitions. [sent-1, score-0.337]
2 Companies and researchers put up a dataset and a problem and data scientists compete to produce the best solutions. [sent-2, score-0.29]
3 We’ve just launched a new initiative called Kaggle in Class, allowing instructors to host competitions for their students. [sent-3, score-0.772]
4 Competitions are a neat way to engage students, giving them the opportunity to put into practice what they learn. [sent-4, score-0.406]
5 The platform offers live leaderboards, so students get instant feedback on the accuracy of their work. [sent-5, score-0.915]
6 And since competitions are judged on objective criteria (predictions are compared with outcomes), the platform offers unique assessment opportunities. [sent-6, score-1.147]
7 The first Kaggle in Class competition is being hosted by Stanford University’s Stats 202 class and requires students to predict the price of different wines based on vintage, country, ratings and other information. [sent-7, score-1.015]
8 Those interested in hosting a competition for their students should visit the Kaggle in Class page or contact daniel. [sent-8, score-0.592]
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Introduction: Anthony Goldbloom from Kaggle writes : We’ve recently put up some interesting new competitions. Last week, Jeff Sonas, the creator of the Chessmetrics rating system, launched a competition to find a chess rating algorithm that performs better than the official Elo system. Already nine teams have created systems that make more accurate predictions than Elo. It’s not a surprise that Elo has been outdone – the system was invented half a century ago before we could easily crunch large amounts of historical data. However, it is a big surprise that Elo has been outperformed so quickly given that it is the product of many years’ work (at least it was a surprise to me). Rob Hyndman from Monash University has put up the first part of a tourism forecasting competition . This part requires participants to forecast the results of 518 different time series. Rob is the editor of the International Journal of Forecasting and has promised to invite the winner to contribute a discussion paper
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Introduction: Yongtao Guan writes: I [Guan] recently began a collaboration with OpenIntro, a group of volunteers from around the country (Duke, Harvard, UCLA, and U.Miami) focused on contributing to improvements in introductory statistics education. They are an active group that has a lot of energy and neat ideas. On behalf of OpenIntro, I’d like to invite the students in your introductory statistics course to participate in a student project competition we are sponsoring this semester. Chris Barr (Assistant Professor at Harvard Biostatistics) and I are co-chairing the competition this Fall. We are hoping to highlight the excellent work that students do by hosting the two best projects from each class at OpenIntro.org and publishing the winners of a larger competition in a paperback volume with brief discussion about each project. Details of the competition can be found at openintro.org/stat/comp. We’ve tried to make the structure general so any class that already has a project integrated
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Introduction: Alex Tabarrok writes : There is something special, magical, and “almost sacred” about the live teaching experience. I agree that this is true for teaching at its best but it’s also irrelevant. It’s even more true that there is something special, magical and almost sacred about the live musical experience. . . . Mark Edmundson makes the analogy between teaching and music explicit: Every memorable class is a bit like a jazz composition. Quite right but every non-memorable class is also a bit like a jazz composition, namely one that was expensive, took an hour to drive to (15 minutes just to find parking) and at the end of the day wasn’t very memorable. The correct conclusion to draw from the analogy between live teaching and live music is that at their best both are great but both are also costly and inefficient ways of delivering most teaching and most musical experiences. Excellent points (and Tabarrok has additional good points that I haven’t quoted). We’re not all
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Introduction: Val has reported success with the following trick: Get to the classroom a few minutes earlier and turn on soft music. Then set everything up and, the moment it’s time for class to begin, put a clicker question on the screen and turn off the music. The students quiet down and get to work right away. I’ve never liked the usual struggle with students to get them to settle down in class, as it seemed to set up a dynamic in which I was trying to get the students to focus and they were trying to goof off. Turning off the music seems like a great non-confrontational way to send the signal that class is starting.
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