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10 things statistics taught us about big data

10 things statistics taught us about big data

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Talk at DC Business Intelligentsia.

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Page 1: 10 things statistics taught us about big data

10 things statistics taught us about big data

Page 2: 10 things statistics taught us about big data

Research Blogging Teaching

Page 3: 10 things statistics taught us about big data

Research Blogging Teaching

jtleek.com

Page 4: 10 things statistics taught us about big data

Research Blogging Teaching

simplystatistics.org

Page 5: 10 things statistics taught us about big data

Research Blogging Teaching

jhudatascience.org

Page 6: 10 things statistics taught us about big data
Page 7: 10 things statistics taught us about big data

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?”    

Page 8: 10 things statistics taught us about big data

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.)  

Page 9: 10 things statistics taught us about big data

from: [email protected] You are f**ed. -roger  

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Enrollment

Time

Page 11: 10 things statistics taught us about big data

Enrollment

Time

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Enrollment

Time

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9 classes 1 month long Every month

Page 14: 10 things statistics taught us about big data

Enrollment

Time

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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

Page 33: 10 things statistics taught us about big data

Plot your data First and always

Page 34: 10 things statistics taught us about big data

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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Page 42: 10 things statistics taught us about big data

shoe size & literacy

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Correct for multiple testing

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http://xkcd.com/882/

Page 48: 10 things statistics taught us about big data

http://xkcd.com/882/

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http://xkcd.com/882/

Page 50: 10 things statistics taught us about big data

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

Page 52: 10 things statistics taught us about big data

101 independent, 70% accurate classifiers

99.9% accuracy

http://www.cbcb.umd.edu/~hcorrada/PracticalML/pdf/lectures/EnsembleMethods.pdf Adapted from Todd Halloway

Page 53: 10 things statistics taught us about big data

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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Page 59: 10 things statistics taught us about big data
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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

Page 64: 10 things statistics taught us about big data

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