Statistics And Graphs: Difference between revisions

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* [book] [http://www.amazon.com/Using-Multivariate-Statistics-Barbara-Tabachnick/dp/0205849571/ref=sr_1_1?s=books&ie=UTF8&qid=1377274046&sr=1-1&keywords=tabachnik+and+fidell Using Multivariate Statistics], recommended by Stephen Correia
* [book] [http://www.amazon.com/Using-Multivariate-Statistics-Barbara-Tabachnick/dp/0205849571/ref=sr_1_1?s=books&ie=UTF8&qid=1377274046&sr=1-1&keywords=tabachnik+and+fidell Using Multivariate Statistics], recommended by Stephen Correia
* [book] [http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738 Pattern Recognition and Machine Learning], recommended by Ryan
* [book] [http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738 Pattern Recognition and Machine Learning], recommended by Ryan
* [paper] [http://dl.acm.org/citation.cfm?id=1553488 Supervised learning from multiple experts: whom to trust when everyone lies a bit], recommended by Rossi Luo
* [book] [http://www.math.dartmouth.edu/~prob/prob/prob.pdf Grinstead and Snell's Introduction to Probability] (downloadable pdf), recommended by Ryan
 
[paper] [http://dl.acm.org/citation.cfm?id=1553488 Supervised learning from multiple experts: whom to trust when everyone lies a bit], recommended by Rossi Luo
* [paper] [http://statistics.berkeley.edu/sites/default/files/tech-reports/790.pdf Measuring Reproducibility of High-throughput Experiments], recommended by Rossi Luo
* [paper] [http://statistics.berkeley.edu/sites/default/files/tech-reports/790.pdf Measuring Reproducibility of High-throughput Experiments], recommended by Rossi Luo


* [practical] [http://depts.washington.edu/aimgroup/proj/ps4hci/ Practical Statistics for HCI], independent study modules by Jacob Wobbrock at UW
* [practical] [http://depts.washington.edu/aimgroup/proj/ps4hci/ Practical Statistics for HCI], independent study modules by Jacob Wobbrock at UW
* [practical] [[Vrl Statistics Tutorial]]
* [practical] [[Vrl Statistics Tutorial]]

Revision as of 19:46, 29 August 2013

Many good resources exist to help you analyze your data. Here are a few:

[paper] Supervised learning from multiple experts: whom to trust when everyone lies a bit, recommended by Rossi Luo