Probability of counts from the counting rate of a radioactive sample?

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The average counting rate of a radioactive sample is 486 counts per minute, translating to 81 counts in a 10-second interval. The probability of obtaining less than 72 counts in this interval can be approximated using a normal distribution, yielding a result of approximately 15.8% without continuity correction and 14.5% with it. The calculation for 60 seconds is not directly proportional; the standard deviation for 60 seconds is 464 counts, making the probabilities different. The discussion highlights the distinction between using Poisson and normal distributions for these calculations. Understanding these statistical models is crucial for accurate probability assessments in radioactive decay scenarios.
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Homework Statement



The average counting rate of a radioactive sample is 486 cpm (counts per minute). Find the probability that in any given 10s interval one gets less than 72 counts. Is this the same as the probability of getting less than 72 X 6 = 432 counts in 60s?


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The Attempt at a Solution



I'm not really sure where to start. I do not think that the probability of less than 72 counts in 10s is the same as getting less than 72 x 6 counts in 60s though.
 
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Radioactive decay can be modeled as a Poisson process. You're given the average event rate (486cpm = 81 counts per 10 sec interval). The variance equals the mean (here that's the average event count for the respective time interval).

Remember that for a sufficiently large mean, the Poisson can be well-approximated by the normal distribution, with a continuity correction applied. That should simplify the calculations.

Does that help?
 
We were not told what a Poisson process is, just that the standard deviation will equal to \sqrt{navg} where navg is the average number of counts, n. If there are 468 counts per minute then the average count rate /10s will be 81 and the standard deviation of that will be 9. So you would get less than 72 counts 15.8% of the time if you use a normal distribution (15.8% of values will lie below one standard deviation).

As for the probability of getting less than 72 X 6 = 432 counts in 60S, this is not the same because one standard deviation from 486 is 464.

Is this correct?
 
carnivalcougar said:
We were not told what a Poisson process is, just that the standard deviation will equal to \sqrt{navg} where navg is the average number of counts, n. If there are 468 counts per minute then the average count rate /10s will be 81 and the standard deviation of that will be 9. So you would get less than 72 counts 15.8% of the time if you use a normal distribution (15.8% of values will lie below one standard deviation).

This is OK *if* you're not supposed to know about a Poisson process and if you're expected to apply the normal distribution without a continuity correction.

However, applying a continuity correction means you have to find ##P(X \leq 71.5)## in a normal distribution with mean 81 and s.d. 9, which is 0.145 or 14.5%.

Doing it by hand for a Poisson distribution is almost impossible, but a Poisson calculator will give a very similar value.

As for the probability of getting less than 72 X 6 = 432 counts in 60S, this is not the same because one standard deviation from 486 is 464.

Correct.
 
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The book claims the answer is that all the magnitudes are the same because "the gravitational force on the penguin is the same". I'm having trouble understanding this. I thought the buoyant force was equal to the weight of the fluid displaced. Weight depends on mass which depends on density. Therefore, due to the differing densities the buoyant force will be different in each case? Is this incorrect?

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