Understanding Data Better with Bayesian and Global Statistical Methods
Astrophysics
2007-05-23 v1
Abstract
To understand their data better, astronomers need to use statistical tools that are more advanced than traditional ``freshman lab'' statistics. As an illustration, the problem of combining apparently incompatible measurements of a quantity is presented from both the traditional, and a more sophisticated Bayesian, perspective. Explicit formulas are given for both treatments. Results are shown for the value of the Hubble Constant, and a 95% confidence interval of 66 < H0 < 82 (km/s/Mpc) is obtained.
Cite
@article{arxiv.astro-ph/9604126,
title = {Understanding Data Better with Bayesian and Global Statistical Methods},
author = {William H. Press},
journal= {arXiv preprint arXiv:astro-ph/9604126},
year = {2007}
}
Comments
14 pages PostScript includes embedded figures. Paper given at Unsolved Problems in Astrophysics conference, Princeton, April 1995