Discussion Overview
The discussion centers around the comparison of error bars represented in sigma values, specifically contrasting 400 sigma with 5 sigma in the context of Cosmic Microwave Background (CMB) data from FIRAS, WMAP, and Planck. Participants explore the implications of such high sigma values on the validity of measurements and the interpretation of statistical significance in scientific data.
Discussion Character
- Debate/contested
- Technical explanation
- Conceptual clarification
Main Points Raised
- Some participants note that a 5 sigma result corresponds to a p-value of approximately 3 x 10^-7, while questioning what p-value a 400 sigma result would imply.
- Others argue that the 400 sigma error bars are exaggerated and not representative of actual measurement precision, suggesting that such high sigma values cast doubt on the validity of the data.
- One participant explains that the sigma of an error bar relates to the confidence level of results, but that the interpretation of high sigma values becomes problematic and less meaningful.
- Another participant emphasizes that real distributions often have broader tails than the normal distribution, making high sigma values less credible in practical applications.
- Questions are raised about the sigma values recorded by WMAP and Planck and whether they confirm the COBE data to the same level of confidence.
- Some participants express frustration over being told they are asking the wrong questions and seek a more constructive dialogue about the topic.
- It is mentioned that the measurements from different satellites (COBE, WMAP, Planck) are consistent but involve different methodologies and error assessments.
Areas of Agreement / Disagreement
Participants generally disagree on the interpretation and significance of high sigma values, particularly regarding the 400 sigma claim. There is no consensus on the validity of such measurements or the appropriate way to compare them across different instruments.
Contextual Notes
Participants highlight limitations in the interpretation of error bars and the assumptions underlying statistical models, particularly at high sigma levels. The discussion reflects uncertainty about the implications of these values and their relevance to scientific conclusions.