Review of Statistical Analysis of Numerical Preclinical Radio-biological Data
Raaz Dwivedi+, Antonio Iannopollo+ and Jiancong Chen∗
+ Department of EECS
* Department of Civil & Environmental Engineering
University of California, Berkeley
This review reproduces tests and results presented by Pitt and Hill in the paper Statistical Analysis of Numerical Preclinical Radio-biological Data and discusses some other non-parametric techniques, such as Permutation Tests, which allow to analyze data with less restrictive assumptions. The focus of the review is on the statistical methodology rather than the underlying biological aspects and assumptions of the original work, which are not discussed. Although not expert in statistical methods for fraud detection, we do believe that permutation tests are promising in this context, as demonstrated by the results presented here. This review has been developed as a term project for a Graduate Level Course on Statistical Models at UC Berkeley.
The organization of this repository is the following:
- Review is the main review folder:
- Report contains our paper review in several formats;
- IPython Notebooks contains the most relevant ipython notebooks and data, used to derive the conclusions in the Report folder;
- Pitt_Hill.pdf is the paper under review;
- README.md is this file;
- Scrapbook contains some working material, and it is included for completeness and transparency.