1 / 6

CDF Statistics Committee: What does it do?

CDF Statistics Committee: What does it do?. Louis Lyons Oxford + SLAC March 2007. CDF Statistics Committee. Who? Luc Demortier, Rockefeller (chair) John Conway, UC Davis Joel Heinrich, Pennsylvania Tom Junk, Illinois Louis Lyons, Oxford Giovanni Punzi, Pisa Where?

nardo
Download Presentation

CDF Statistics Committee: What does it do?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CDF Statistics Committee: What does it do? Louis Lyons Oxford + SLAC March 2007

  2. CDF Statistics Committee Who? Luc Demortier, Rockefeller (chair) John Conway, UC Davis Joel Heinrich, Pennsylvania Tom Junk, Illinois Louis Lyons, Oxford Giovanni Punzi, Pisa Where? http://www-cdf.fnal.gov/physics/statistics/ When? Once a month since 2000

  3. ACTIVITIES Frequently asked questions Recommendations Liasons Notes on statistical issues Links to Conferences, papers etc List of books

  4. Frequently asked questions Estimating efficiencies near 1 Pull quantities Error on ratio of Poisson counts Unbinned maximum likelihood as goodness of fit? Combining quantities with unknown correlation Parametrising background shapes for fits Significance calculation allowing for background uncertainties Significance from difference in log(L) Combining significances from different (independent) analyses

  5. RECOMMENDATIONS Neural networks, support vector machines Optimising searches Likelihood fits with individual event errors (Punzi effect) Coverage for Poisson intervals e.g. ΔlnL = -0.5 Plotting Poisson error bars Good and bad random number generators Systematics and limits: the Manhattan project Bayes and Frequentism Comparing 2 hypotheses Simple facts about p-values Blind analyses

  6. Conclusions Useful for :-- Giving advice Spotting some errors Aiming for uniform practice Answering queries Possible improvements :-- More active liasons Someone at Fermilab to discuss, rather than e-mail More on multi-variate methods for separating signal from bgd More software

More Related