Statistics: Can You Really Believe the Figures? [ABSTRACT]
Jinfo Blog
1st February 2008
By Chris Murphy
Abstract
Hard, objective, accurate, definitive, precise numbers are beguilingly appealing. Yet in reality numbers are often subjective, vague, provisional and need to be qualified - they can even be downright misleading. So a few key danger zones are highlighted here and some elementary precautions suggested. They may seem 'self-evident'. However, a vast number of examples could be quoted to show that simple errors often trip up even sophisticated research.
Item
Hard, objective, accurate, definitive, precise numbers are beguilingly appealing. Yet in reality numbers are often subjective, vague, provisional and need to be qualified - they can even be downright misleading. So a few key danger zones are highlighted here and some elementary precautions suggested. They may seem 'self-evident'. However, a vast number of examples could be quoted to show that simple errors often trip up even sophisticated research.
What's Inside:
Another potential statistical elephant trap is combining data from sources that do not compile it on the same basis. Failing to do so can have a dramatic impact.
---
This is a brief abstract of the full article. FUMSI subscribers can log in to MyShop at FreePint view the full article. Others can subscribe to FUMSI now for access to the complete archive of FUMSI articles.
- Blog post title: Statistics: Can You Really Believe the Figures? [ABSTRACT]
- Link to this page
- View printable version
- Statistics: Can You Really Believe the Figures?
Friday, 1st February 2008
- What They Say and Do: Practical Tips for Harvesting Reliable User Feedback for Planning
Saturday, 30th September 2006 - Business Information Trends: Adding Value and Creating Customised Applications
Saturday, 30th September 2006
Register for our next Community session:
![]()
Transforming knowledge management at BASF – GenAI and the evolution of QKnows
10th December 2025
Latest on our YouTube channel:![]()
Read on the Blog:
December 2025 update
3rd December 2025
- Jinfo wins CILIP’s inaugural “McFarlane & Ward Information Management” award
4th December 2025 - December 2025 update
3rd December 2025 - Review of Matchplat – combining AI with traditional industry code searching
27th November 2025
- Team roles and AI (Community) 26th February 2026
- Team demand and AI (Community) 22nd January 2026
- Transforming knowledge management at BASF – GenAI and the evolution of QKnows (Community) 10th December 2025