« Predictive modeling | Main | Where do the numbers come from? »


Feed You can follow this conversation by subscribing to the comment feed for this post.

Drug Test Friend

Athlese use steroide to improve their performance, plain and simple. The pressure of competition can and often does drive athletes to resorting to taking unethical measures to win.

David Rouse

I'm assuming part of the problem is that current doping methods are very hard to test for and involve establishing baselines and looking at changes over time, and rigorous testing would involve false positives. Banning someone from a sport (or even just one race) seems disproportionate a penalty when you know there will be false positives.

Why not just do 100% testing before and after each stage and handicap times based on relative measurements between the competitors? That should discourage doping and also lower the damage of a false positive. It could also make the sport less about the human machine and more about skill.

Verify your Comment

Previewing your Comment

This is only a preview. Your comment has not yet been posted.

Your comment could not be posted. Error type:
Your comment has been posted. Post another comment

The letters and numbers you entered did not match the image. Please try again.

As a final step before posting your comment, enter the letters and numbers you see in the image below. This prevents automated programs from posting comments.

Having trouble reading this image? View an alternate.


Post a comment

Marketing and advertising analytics expert. Author and Speaker. Currently at Vimeo and NYU. See my full bio.

Next Events

Mar: 26 Agilone Webinar "How to Build Data Driven Marketing Teams"

Apr: 4 Analytically Speaking Webcast, by JMP, with Alberto Cairo

May: 19-21 Midwest Biopharmaceutical Statistics Workshop, Muncie, IN

May: 25-28 Statistical Society of Canada Conference, Toronto

June: 16-19 Predictive Analytics World (Keynote), Chicago

Past Events

Feb: 27 Data-Driven Marketing Summit by Agilone, San Francisco

Dec: 12 Brand Innovators Big Data Event

Nov: 20 NC State Invited Big Data Seminar

Nov 5: Social Media Today Webinar

Nov: 1 LISA Conference

Oct: 29 NYU Coles Science Center

Oct: 9 Princeton Tech Meetup

Oct: 8 NYU Bookstore, NYC


Jul: 30 BIG Frontier, Chicago

May: 30 Book Expo, NYC

Apr: 4 New York Public Library Labs and Leaders in Software and Art Data Viz Panel, NYC

Mar: 22 INFORMS NY Student-Practitioner Forum on Analytics, NYC

Oct: 19 Predictive Analytics World, NYC

Jul: 30 JSM, Miami

Junk Charts Blog

Link to junkcharts

Graphics design by Amanda Lee


  • only in Big Data