Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The Human Factor Continually Confounds Probability Models
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Modeling > The Human Factor Continually Confounds Probability Models
ExclusiveModelingPredictive AnalyticsStatistics

The Human Factor Continually Confounds Probability Models

paulbarsch
paulbarsch
3 Min Read
SHARE

With four weeks to go in the 2011 Major League Baseball season, the probability of the Boston Red Sox of making the playoffs was 99.6%. And most of us know the story; in one of the biggest collapses in baseball history, the Red Sox tanked a nine game lead and served the wild card slot to the Tampa Bay Rays. In creating “one for the record books”, the 2011 Red Sox show us that the human factor continually confounds probability models.

With four weeks to go in the 2011 Major League Baseball season, the probability of the Boston Red Sox of making the playoffs was 99.6%. And most of us know the story; in one of the biggest collapses in baseball history, the Red Sox tanked a nine game lead and served the wild card slot to the Tampa Bay Rays. In creating “one for the record books”, the 2011 Red Sox show us that the human factor continually confounds probability models.

Some things aren’t supposed to happen. The 2011 Boston Red Sox certainly should not have missed the playoffs with a nine game lead, and the 1995 Anaheim Angels should not have finished their year 12-26 (losing a nine game lead and missing the playoffs). Moreover, probability models said the stock market (DJIA) should not have lost 54% of its value in the 2008 “Great Recession”.

More Read

Analytics skills in demand – and analytics pros demanding top salaries
“For years, Western governments have used supercomputers to model weapons of nuclear war. Now a…”
As ICOs Struggle, Crypto Provides Better Solutions
Using Data Analytics to Optimize Your Cash Collection Approach
Improving Big Data Analytics To Address Cybersecurity Challenges

There’s definitely a danger in too much reliance on normal distribution probability models, especially when humans are concerned says Financial Times writer John Authers. 

Studying the 2011 Boston Red Sox, Authers suggests the team may have been overconfident in statistics since few teams in baseball history had collapsed with such a lead.  

Authers also believes bell curve probabilistic models would not have been a reliable indicator of possible failure because such models assume event independence where one event should not affect another. But those who follow sports understand the concept of “momentum in a game”, or even from game-to-game where a team can feed off past success to gain confidence.

In reference to the 2008 market crash, Steven Solmonson, head of Park Place Capital Ltd said; “Not in a million years would we have expected this gyration to be as vicious and enduring as it has been.”  And I’m sure that Boston Red Sox fans didn’t believe their team could lose a significant lead over the Tampa Bay Rays with just a few games left in the season.

Whenever humans are involved, the lesson is clear: don’t get over confident in normal distribution probability models. Next thing you know, you might get slapped (or worse) by the fat tail.

 

 

TAGGED:bayesianbell curveprobabilitystatistics
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai in video game development
Machine Learning Is Changing iGaming Software Development
Exclusive Machine Learning News
media monitoring
Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
Analytics Exclusive Infographic
data=driven approach
Turning Dead Zones Into Data-Driven Opportunities In Retail Spaces
Big Data Exclusive Infographic
smarter manufacturing
Connecting the Factory Floor: Efficient Integration for Smarter Manufacturing
Infographic News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Business People Are Dumb On Average(s)

7 Min Read

The statistics of vaccines

4 Min Read

When improbable events are expected

5 Min Read

Patterns patterns everywhere

17 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?