Successfully reported this slideshow.
Upcoming SlideShare
×

# Nate Silver - What Do Poker, Presidential Elections, & Sports Have in Common with Big Data? - Data Summit

1,006 views

Published on

Nate Silver, Statistician, Author & Founder, ESPN'S FiveThirtyEight blog

His presentation at the 4A's Data Summit on Oct. 16 in NYC. Visit http://datasummit.aaaa.org/ for more information.

Published in: Sports, Technology, Spiritual
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Don't get greedy! Cash-out your winnings METHOD INSIDE https://t.co/UxKYAUMSkX

Are you sure you want to  Yes  No
• Be the first to like this

### Nate Silver - What Do Poker, Presidential Elections, & Sports Have in Common with Big Data? - Data Summit

1. 1. Big Data… Big Problems?
2. 2. Big Data… Big Problems?
3. 3. Big Data… Big Problems?
4. 4. The Lessons of 2012 The 538 Method (Simplified) 1. Average the Polls 2. Count to 270 3. Account for Margin of Error
5. 5. The Lessons of 2012
6. 6. The Lessons of 2012
7. 7. The Lessons of 2012
8. 8. The Lessons of 2012 “nate silver” “joe biden”
9. 9. The Lessons of 2012 “justin bieber”
10. 10. Problem #1: Big Data… Big Bias?
11. 11. Problem #1: Big Data… Big Bias?
12. 12. Problem #1: Big Data… Big Bias?
13. 13. The Signal-to-Noise Ratio
14. 14. The Signal-to-Noise Ratio
15. 15. The Signal-to-Noise Ratio
16. 16. Problem #2: Desperately Seeking Signal http://imgs.xkcd.com/comics/sports.png
17. 17. Problem #2: Desperately Seeking Signal
18. 18. Problem #2: Desperately Seeking Signal
19. 19. The Limits of Artificial “Intelligence” a 8 7 6 5 4 3 2 1 b c d e f g h
20. 20. The Limits of Artificial “Intelligence” Kasparov +1 +1 +1 +1 +1 +1 +3 +3 +3 +5 +9 = 29 Deep Blue +1 +1 +1 +1 +1 +3 +3 +5 +5 +9 = 30
21. 21. The Limits of Artificial “Intelligence” a 8 7 6 5 4 3 2 1 b c d e f g h
22. 22. The Limits of Artificial “Intelligence” a 8 7 6 5 4 3 2 1 b c d e f g h
23. 23. The Limits of Artificial “Intelligence” a 8 7 6 5 4 3 2 1 b c d e f g h
24. 24. Problem #3: Feature or Bug?
25. 25. Problem #3: Feature or Bug?
26. 26. Problem #3: Feature or Bug?
27. 27. Suggestions
28. 28. Suggestions 1. Think Probabilistically 2. Know Where You’re Coming From 3. Try, and Err
29. 29. Suggestion #1: Think Probabilistically Flood Prediction: 49’ Levee: 51’
30. 30. Suggestion #1: Think Probabilistically Margin of Error: ±9’ Flood Prediction: 49’ Levee: 51’
31. 31. Suggestion #1: Think Probabilistically
32. 32. Suggestion #2: Know Where You’re Coming From
33. 33. Suggestion #3: Try, and Err 100% 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
34. 34. Suggestion #3: Try, and Err
35. 35. Suggestion #3: Try, and Err 100% 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
36. 36. Suggestion #3: Try, and Err
37. 37. Suggestion #3: Try, and Err 100% 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
38. 38. Suggestion #3: Try, and Err 100% 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
39. 39. Suggestion #3: Try, and Err 100% Water level 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
40. 40. Suggestion #3: Try, and Err 100% Competitive Advantage 80% 60% Accuracy 40% 20% 0% 0% 20% 40% 60% Effort 80% 100%
41. 41. Suggestions 1. Think Probabilistically 2. Know Where You’re Coming From 3. Try, and Err
42. 42. Suggestions (Know Your Limitations) 2. Know Where You’re Coming From 3. Try, and Err
43. 43. Suggestions (Know Your Limitations) (Consider Your Assumptions) 3. Try, and Err