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
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Floating-point errors, explained
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Floating-point errors, explained
Uncategorized

Floating-point errors, explained

DavidMSmith
DavidMSmith
3 Min Read
SHARE

Back in March, we looked at the reasons behind apparent arithmetic “mistakes” that can occur in software programs like R that use floating-point arithmetic, like this:    

> 1.0 – 0.9 – 0.1
[1] -2.775558e-17

Of course, the answer should be zero, but it’s not, not exactly anyway. That example (which I wish I’d thought of myself at the time) comes from an well-written and informative article published in PC Plus and available online at techradar.com. In simple, non-technical terms, it explains why such floating-point errors occur. It also gives some examples of the consequences of not anticipating such errors, like the Ariane 5 rocket that self-destructed 5 seconds after launch, or the Patriot missile that failed to target an Iraqi Scud missile that killed 28 people. 

More Read

Reduce, Re-Tweet
How Big Data, and Critical Thinking, Lead to Business Value
Converting time zones in R: tips, tricks and pitfalls
Integrating a Content Plan with Demand Gen [VIDEO]
Widespread Cyber Espionage: More evidence and what to do about it

These horror stories explain why good programmers should always be aware of the pitfalls of using floating-point arithmetic and to program defensively to avoid them. (I gave some tips for R in that article from March.) It’s a great article to send next time someone asks you why their code isn’t giving a exactly the right result when they think it should.

TechRadar.com: Why computers …



Back in March, we looked at the reasons behind apparent arithmetic “mistakes” that can occur in software programs like R that use floating-point arithmetic, like this:    

> 1.0 – 0.9 – 0.1
[1] -2.775558e-17

Of course, the answer should be zero, but it’s not, not exactly anyway. That example (which I wish I’d thought of myself at the time) comes from an well-written and informative article published in PC Plus and available online at techradar.com. In simple, non-technical terms, it explains why such floating-point errors occur. It also gives some examples of the consequences of not anticipating such errors, like the Ariane 5 rocket that self-destructed 5 seconds after launch, or the Patriot missile that failed to target an Iraqi Scud missile that killed 28 people. 

These horror stories explain why good programmers should always be aware of the pitfalls of using floating-point arithmetic and to program defensively to avoid them. (I gave some tips for R in that article from March.) It’s a great article to send next time someone asks you why their code isn’t giving a exactly the right result when they think it should.

TechRadar.com: Why computers suck at maths

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

street address database
Why Data-Driven Companies Rely on Accurate Street Address Databases
Big Data Exclusive
predictive analytics risk management
How Predictive Analytics Is Redefining Risk Management Across Industries
Analytics Exclusive Predictive Analytics
data analytics and gold trading
Data Analytics and the New Era of Gold Trading
Analytics Big Data Exclusive
student learning AI
Advanced Degrees Still Matter in an AI-Driven Job Market
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

How to Generate Big Data Revenue Without the Big Investment in a Team of Data Scientists

6 Min Read

Introducing the Business Operating Platform

21 Min Read

Benford’s Law, Zipf’s Law and the Pareto Distribution

2 Min Read

Microsoft: ‘we’re bringing SOA to the masses’

1 Min Read

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

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?