Statistical error analysis of Geiger counter?

In summary, the authors present an equation for the error propagation of a function when the measurements are integer numbers. They argue that the error analysis becomes inapplicable because the standard deviation vanishes and the statistical error becomes infinite. Additionally, they present equations for the counts of a Geiger counter and discuss the effects of time intervals on the error. They conclude that it is best to have one long time interval instead of many short intervals of the same cumulative duration to minimize the standard deviation.
  • #1
carnivalcougar
40
0
1. Homework Statement

An average value of N measurements is defined as:

ravg = 1N ∑ ri where i = 1 and it sums up to N measurements

By using this expression in the master formula for a general function z = (x1, x2,...) error propagation, we find the δravg error propagation:
(δravg)2 = ( (∂ravg (ra, r2,...) / ∂r1 ) (δr1))2 + ( (∂ravg (ra, r2,...) / ∂r1) (δr1))2 + ...

Finally, we arrive at the following conclusion:
δravg = δrN√
since all measurements are independent (δr1)2 = (δr2)2 = ... = (δr)2. In your present investigation the counts of the geiger counter are integer numbers. They can become zero, navg = 0, if the shiled is thick or the time interval becomes small. Does this mean that standard deviation vanishes, [itex]\sqrt{navg}[/itex] --> 0, and statistical error becomes infinite, δnavg ∝ navg-1/2 → ∞ ? Or, does the presented statistical error analysis become inapplicable in this case? Is it better to have one longer time interval or many short intervals of the same cumulative duration to minimize the standard deviation (or does it make no difference)?



2. Homework Equations
Provided in question


3. The Attempt at a Solution

I think that the error analysis becomes inapplicable. I don't think the standard deviation vanishes and the statistical error becomes infinite. This may be completely wrong though. I'm not sure if the interval matters though.
 
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  • #2
I see two relevant equations, one for ravg (where I assume you mean ravg = 1/N ∑ ri) and one for δravg. Ok.

I don't see where δravg = δrN√ comes from . Can you complete it and work it out ?

I also don't see why all δri should be equal. What do you measure ? Do you use equal time intervals for the measurements ?

Did you learn about Poisson statistics already ?
 
  • #3
I think if you want people to take the time to help you, you ought to at least take the time to make sure your equations are written correctly.
 
  • #4
I attached pictures of the question with the equations typed out so they will definitely be correct.

We also did not learn Poisson processes.
 

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  • #5
I see. So what I assumed was your attempt at a solution was really the original problem statement.
No relevant equations at all ? No attempt at a solution, except some thoughts ?

And apparently, you/they use equal time intervals for the measurements, so the errors might be the same for each ri.

So where are you with your present investigation ?

What they are also asking is "If you have an hour of counting time, is it better to take 60 measurements of 1 minute, 30 of 2 or 12 of 5 or 1 of 60 minutes, or doesn't it matter ?"

What is observed with a Geiger counter (the name says it already) is counts. Rate = counts/time interval, and those we had fixed. So with a given rate r and a given N you can say something about the expected number of counts per interval.

If you are not familiar with Poisson, then: do you know about binomial distributions ? Gauss distribution ?
 
  • #6
carnivalcougar said:
We also did not learn Poisson processes.

You will, of course, recall that I asked the same question that BvU is asking when you posed another question on radioactivity in a different thread in Intro Physics.

You have to learn about Poisson processes (and the approximation of the Poisson distribution to the normal distribution for large mean values). Whether you've been formally taught these things or not seems to be irrelevant if they're asking you questions on these topics.

I suggest self-study - the net is a great resource.
 

1. What is statistical error analysis?

Statistical error analysis is a process used to evaluate the accuracy and precision of a measurement or experiment. It involves identifying and quantifying the sources of error in a measurement and calculating the uncertainty associated with the results.

2. Why is statistical error analysis important in Geiger counter measurements?

Geiger counters are highly sensitive instruments that are used to detect and measure radiation. The accuracy of their measurements is critical in many applications, such as nuclear power plants and radiation monitoring. Statistical error analysis helps ensure the reliability and validity of the data collected by Geiger counters.

3. What are some common sources of error in Geiger counter measurements?

Some common sources of error in Geiger counter measurements include background radiation, instrument calibration, and human error. Additionally, environmental factors such as temperature and humidity can also affect the accuracy of the measurements.

4. How is uncertainty calculated in statistical error analysis of Geiger counter measurements?

Uncertainty is calculated by analyzing the sources of error and their respective magnitudes. This can be done through statistical methods, such as calculating the standard deviation or using error propagation equations. The uncertainty value is typically expressed as a percentage of the measured value.

5. How can statistical error analysis be used to improve the accuracy of Geiger counter measurements?

By identifying and quantifying the sources of error, statistical error analysis can help improve the accuracy of Geiger counter measurements. This can be achieved by implementing proper calibration procedures, reducing sources of interference, and conducting multiple measurements to reduce random error. It is also important to regularly review and analyze the data to identify any patterns or trends that may indicate a need for adjustments in the measurement process.

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