about

As of the 23rd May 2022 this website is archived and will receive no further updates.

https://understandinguncertainty.org was produced by the Winton programme for the public understanding of risk based in the Statistical Laboratory in the University of Cambridge. The aim was to help improve the way that uncertainty and risk are discussed in society, and show how probability and statistics can be both useful and entertaining.

Many of the animations were produced using Flash and will no longer work.

About Us

What is this site?

This site was produced by the Winton programme for the public understanding of risk based in the Statistical Laboratory in the University of Cambridge. The aim was to help improve the way that uncertainty and risk are discussed in society, and show how probability and statistics can be both useful and entertaining! However we also acknowledge that uncertainty is not just a matter of working out numerical chances, and aim for an appropriate balance between qualitative and quantitative insights.

Future Plans

Future plans for web-site (june 2008)

  • Regular updates / RSS feed
  • Encourage contributions on topics such as climate change and electromagnetic fields
  • 'Novelty’ features: eg Poetry corner, quotes
  • Use narrative as much as possible - story-based
  • Contribute to Wikipedia when ready, also get linked from there.

Notes for Reviewers

This site is in an early stage of development, and we would welcome your comments on any aspect of the content and presentation. A few points you may wish to keep in mind:

Qualitative Concepts

These might include:

  • Precautionary principle
  • Evaluating Evidence
  • Psychology of risk behaviour
  • Neurophysiology of risk behaviour
  • Sociology of risk / Risk in society
  • Philosophy of risk
  • What is ‘probability’/ risk etc?
  • Risk communication
  • Teaching resources on risk/uncertainty

Quantitative Concepts

These might include:

  • Learning from data
  • Absolute and relative risks
  • Individual and ‘average’ risks
  • Bayes theorem
  • Regression-to-the-mean
  • Unexpected / rare events, coincidences
  • Trends
  • When to stop?
  • Ranking
  • Predictability

Issues

These might include:

  1. Lifestyle
    1. Sex
    2. Drugs
    3. Smoking
    4. Alcohol
  2. Childhood
    1. Accidents
    2. Violence
    3. Obesity
  3. Healthcare
    1. NICE approvals
    2. Vaccines (MMR etc)
    3. League tables
    4. Drug Safety
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