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Statistical Issues for GLAST

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

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Statistical Issues for GLAST

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  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. ΔlnL = 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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