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Statistical Issues for GLAST

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Statistical Issues for GLAST (1) 'Automated analysis of the GLAST photon data stream. using segmentation techniques (Voronoi tessellation, etc.)' Jeff Scargle ... – PowerPoint PPT presentation

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Title: Statistical Issues for GLAST


1
Statistical Issues for GLAST
  • (1) "Automated analysis of the GLAST photon data
    streamusing segmentation techniques (Voronoi
    tessellation, etc.)" 
  •                                                   
                          Jeff Scargle
  • (2) "Upper limits on sources and spectral
    lines"     Jeff Scargle
  •  
  • (3) "Maximum Likelihood for LAT Data Upper
    Limits, Significances, and Confidence
    Intervals"                               
     Jim Chiang
  •  
  • (4)  When the likelihood ratio fails Pilla
    Loader Pat Nolan
  • (5) "What does the Statistics Committee at
    the CDF experiment at Fermilab do?
                       Louis
    Lyons
  • (6) Discussion

2
CDF Statistics Committee What does it do?
  • Louis Lyons
  • Oxford SLAC


  • March 2007

3
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

4
ACTIVITIES
  • Frequently asked questions
  • Recommendations
  • Liasons
  • Notes on statistical issues
  • Links to Conferences, papers etc
  • List of books

5
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

6
RECOMMENDATIONS
  • Neural networks, support vector machines
  • Optimising searches
  • Likelihood fits with individual event errors
    (Punzi effect)
  • Coverage for Poisson intervals e.g. ?lnL
  • 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

7
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
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