What Can Be Learned from Signal vs. Background Efficiency Plots?

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SUMMARY

The discussion focuses on the analysis of signal vs. background efficiency plots, specifically the relationship represented by the function εbkg(εsig). Participants emphasize the importance of selecting appropriate thresholds to optimize signal efficiency while minimizing background events. The use of TMVA (Toolkit for Multivariate Analysis) is highlighted as a method to create continuous curves that represent these efficiencies. The discussion concludes that effective selections can significantly enhance the quality of data analysis in particle physics.

PREREQUISITES
  • Understanding of signal and background efficiency in data analysis
  • Familiarity with TMVA (Toolkit for Multivariate Analysis)
  • Basic knowledge of plotting functions and curves
  • Concept of event selection in statistical analysis
NEXT STEPS
  • Research advanced techniques in TMVA for optimizing signal selection
  • Explore methods for visualizing efficiency curves in data analysis
  • Learn about statistical significance in background event reduction
  • Investigate the impact of different selection thresholds on efficiency plots
USEFUL FOR

Data analysts, physicists, and researchers involved in particle physics who are looking to enhance their understanding of efficiency plots and improve data selection strategies.

ChrisVer
Science Advisor
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What information can one obtain from the plots of the background vs signal efficiency? \epsilon_{bkg}(\epsilon_{sig})?
In particular I attach some plots I made by hand and I want to understand how to obtain what each tells us.
 

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Your plot should have 1/(background efficiency) or 1-(background efficiency) as vertical axis.

Each point on the curve is a possible selection. As an example, you can randomly take 60% of the events, then you have 60% signal efficiency and keep 60% of the background. That is not a good selection, of course. Your actual one might keep 90% of the signal events and keep only 5% of the background. If you make the selection a bit looser, you get 91% of the signal, but 10% of the background. Make this in a continuous way (with TMVA usually) and you get a curve. With the usual choices for axes, all curves should look like the blue one.
 

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