10 things statistics taught us about big data
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10 things statistics taught us about big data
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Research Blogging Teaching
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Research Blogging Teaching
jtleek.com
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Research Blogging Teaching
simplystatistics.org
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Research Blogging Teaching
jhudatascience.org
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from: [email protected] Roger let me know you gave him a ballpark figure for the number of students registered for his course "Computing for Data Analysis”. Could you give me an idea of how many have registered for my course "Data Analysis?”
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from: [email protected] Hi Jeff, 7,000 students! It's pretty awesome. (You'll be able to check this out yourself next week, once the class sites are up.)
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from: [email protected] You are f**ed. -roger
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Enrollment
Time
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Enrollment
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Enrollment
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9 classes 1 month long Every month
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Enrollment
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1,000,000+ Enrolled
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http://goo.gl/vQK0RH
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http://goo.gl/xWAlPi
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10 statistics things
http://goo.gl/wTAuvR
1. Problem first, not solution backward 2. Define a metric for success first 3. Analyze interactively 4. Plot your data first and always 5. Know your real sample size 6. Watch out for confounders 7. Correct for multiple testing 8. Average many predictors 9. Smooth over time and space 10. Have others check your work
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Problem first Not solution backward
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http://goo.gl/3vA1OB
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http://hyperboleandahalf.blogspot.com/
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http://cran.r-project.org//
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http://bioconductor.org/
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Define a metric for success Before you start
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http://www.agendia.com/managed-care/breast-cancer/mammaprint/
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89% sensitivity 42% specificity 65% accuracy
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http://www.biomedcentral.com/1471-2164/14/336/figure/F3
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Analyze Interactively
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http://had.co.nz/
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https://twitter.com/EllieMcDonagh/status/469184554549248000
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http://www.chrisstucchio.com/blog/2013/hadoop_hatred.html
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Plot your data First and always
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http://www.chrisstucchio.com/blog/2013/hadoop_hatred.html
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h$p://www.biostat.wisc.edu/~kbroman/topten_worstgraphs/
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Know your real sample size
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Watch out for confounders
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http://xkcd.com/552/
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shoe size & literacy
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Correct for multiple testing
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http://xkcd.com/882/
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http://xkcd.com/882/
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http://xkcd.com/882/
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Average many predictors
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5 independent, 70% accurate classifiers
10 (.7^3)(.3^2)+5(.7^4)(.3)+(.7^5)=
83.7% accuracy http://www.cbcb.umd.edu/~hcorrada/PracticalML/pdf/lectures/EnsembleMethods.pdf Adapted from Todd Halloway
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101 independent, 70% accurate classifiers
99.9% accuracy
http://www.cbcb.umd.edu/~hcorrada/PracticalML/pdf/lectures/EnsembleMethods.pdf Adapted from Todd Halloway
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http://www.cbcb.umd.edu/~hcorrada/PracticalML/pdf/lectures/EnsembleMethods.pdf Adapted from Todd Halloway
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Smooth (average) over time and space
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http://simplystatistics.org/2014/02/13/loess-explained-in-a-gif/
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http://fivethirtyeight.com/
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Have others check your work
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10 statistics things
http://goo.gl/wTAuvR
1. Problem first, not solution backward 2. Define a metric for success first 3. Analyze interactively 4. Plot your data first and always 5. Know your real sample size 6. Watch out for confounders 7. Correct for multiple testing 8. Average many predictors 9. Smooth over time and space 10. Have others check your work
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