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> >  New prior shapes for nuisance parametersThe statistics board asked for gamma and lognormal priors. These distributions have 3 degrees of freedom, two of which are fixed by the requirements of given mean and RMS. From a literature scan I found that the common practice is to assume mu=0, where I use the variable names used in ROOT's TMath.
To see what these look like I used the attached priors.c (may require ROOT5.26 to run). Some output examples are:
The numbers in parenthesis are the errors on the last digits. The first number is the mean of the histogram, and the 2nd is the RMS. The Gauss and LogNormal histogram is filled by transforming a normal variable, rather than from the plotted function.  
19Apr2010 InformationIntroduction and referencesSome material in preparation of the April 20th meeting.  
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In particular, the systematic effects have large bintobin correlations, which should dominate any quantitative treatment of the systematics (see [2], Fig. 2, offdiagonal elements). In particular, the relative JES effects at a particular jet pT should be propagated to a range of Mjj bins.  
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The preferred technique(with a few questions to the SB interleaved) 
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This supplements Robert's email and uses the references he provided:  
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statistics dominates IN EVERY SINGLE BIN OF INTEREST.
 
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I see two main options:
 
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In particular, the systematic effects have large bintobin correlations, which should dominate any quantitative treatment of the systematics (see [2], Fig. 2, offdiagonal elements). In particular, the relative JES effects at a particular jet pT should be propagated to a range of Mjj bins.  
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I plan to explore the 2nd approach, using a profile likelihood fit with the "usual" binomial statistics. But we do not yet have a consensus on whether this is necessary for an ICHEP publication.
 
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17Mar2010 InformationFollowing the discussion just before midnight in the 16Mar statistics board meeting, here is a status report for the statistics in the dijet ratio, with context and links to notes and talks.  
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Additional statistical analysis of high mass region?We would appreciate your input on whether any additional test statistics that answer the question:  
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This supplements Robert's email and uses the references he provided: Our preferred limit setting technique for ICHEP, and the publication plan that motivates it, are described in [1]. This plan hinges on our expectations that for ICHEP the transition between the statisticsdominated and statisticaldominated regions and the transition between the regions explored by the Tevatron and those we will explore for the first time fall very close to each other, around 800GeV. It is clear that further development will be needed for future publication. In particular, the systematic effects have large bintobin correlations, which should dominate any quantitative treatment of the systematics (see [2], Fig. 2, offdiagonal elements). In particular, the relative JES effects at a particular jet pT should be propagated to a range of Mjj bins.
The preferred technique is(with a few questions to the SB interleaved)
Additional statistical analysis of high mass region?We would appreciate your input on whether any additional test statistics that answer the question: "Is the data above the Tevatron limits consistent with our SM predictions?"
Additional statistical analysis of low mass region?There are two more, closelyrelated questions that can be asked, and we would appreciate your input on them.
To a large extend, this question will be answered in the "R" plot, which summarizes our data and predictions. We will draw ClopperPearson intervals on the data points, and the systematics on the predictions, which allow the reader to see any significant deviation. It would be nice to have a statistical statement that covers both the highstatistics, TevatronexcludedNP region and the lowstatistics, we'reexploringnewenergies region. Especially as the fact that the cross over between the two regimes is basically at the same point is a temporary coincidence expected for an ICHEP result. I plan to explore the 2nd approach, using a profile likelihood fit with the "usual" binomial statistics. But we do not yet have a consensus on whether this is necessary for an ICHEP publication.
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Following the discussion just before midnight in the 16Mar statistics board meeting, here is a status report for the statistics in the dijet ratio, with context and links to notes and talks.  
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IntroductionFollowing the discussion just before midnight in the 16Mar statistics board meeting, here is a status report for the statistics in the dijet ratio, with context and links to notes and talks. There are several reasons to adopt for an ICHEP analysis different tools, and a different approach, than was taken so far in the dijet ratio. This demotes some of the documentation to a documentation of historical attempts  if you wish to skip that, don't read sections 3.2 to 3.4 in the analysis note, and just look for "LLR" plots in the presentations, ignoring other test statistics. Given an observable sensitive to a wide range of models, I started by looking for a test statistic that maintains that generality. This is documented in the AN. The presentation shows extensions, and also that systematic uncertainties have a huge effect (*). This shifts the focus to how to handle the systematics, and indicates we should switch to using the more familiar loglikelihood ratios (LLRs) so we can focus on the systematics. (*) This is a very preliminary and unexpected result which I haven't fully debugged yet. Given Jim's 7TeV numbers, and assuming ~3pb1 for ICHEP, we are looking at systematic uncertainties of roughly 0.03 (absolute on R) and statistical uncertainties will dominate (i.e. >0.06) from around 800GeV. The Tevatron exclusions are Lambda<2.7TeV and Mq*<0.87TeV. So we can analyze our data starting from 870GeV, where systematics should not dominate, and ruling out a q* of 1TeV is in play (see Fig. 11 in AN, though the wrong Ecm is used), and so is a 3TeV contact interaction (see Jim's presentation). To put it differently  for ICHEP we have the option of doing the analysis so that statistics dominates IN EVERY SINGLE BIN OF INTEREST.
Selected documentation:
Now what?I see two main options:
