How Do You Calculate One Sigma Confidence Intervals for Poisson Events?

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SUMMARY

This discussion focuses on calculating one sigma confidence intervals for Poisson events, specifically when analyzing occurrence rates such as 20 out of 10,000 and 43 out of 10,000. The variance of a Poisson distribution is equal to its parameter, thus the one sigma confidence interval can be calculated using the formula n ± √n, where n represents the number of observed events. For more precise confidence intervals at a specific significance level, the article by Crow and Gardner is recommended as a resource.

PREREQUISITES
  • Understanding of Poisson distribution and its properties
  • Familiarity with statistical confidence intervals
  • Basic knowledge of variance and standard deviation calculations
  • Ability to interpret statistical significance levels
NEXT STEPS
  • Read the article by Crow and Gardner on confidence intervals for Poisson events
  • Explore the concept of asymptotic normal distribution in statistical analysis
  • Learn about different methods for calculating confidence intervals
  • Investigate the implications of small sample sizes on statistical estimates
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Statisticians, data analysts, researchers in fields involving event occurrence rates, and anyone involved in calculating confidence intervals for Poisson-distributed data.

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I have been analyzing some data at work, and I have measured the occurrence rates of some event. How do I give a one sigma confidence interval to go along with it, assuming it is a Poisson event? For example, I found that something occurs 20 out of 10 000 times, something else occurs 43 out of 10 000 times, etc. How do I calculate one sigma error bars for these values? I know that for large number of events the uncertainty goes to root N, but what about for smaller numbers like, say, a rate of 5 in a 1000.
 
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Using a sigma confidence interval you are implicitly assuming an asymptotic normal distribution. Or do you want e.g. a 64% error interval?
In the first case, if x is the parameter of the Poisson distribution, then it's variance is x, too. The estimate of x is n, the number of events observed. Then possible 1 sigma confidence intervals are
n+-sqrt(n).
If you want better CIs, with a given significance level (rather than sigma value) p, refer to the article by Crow and Gardner:
http://www.ps.uci.edu/~markm/freq/crowgardner.ps
 
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