What's the standard deviation of values in the histogram bar

AI Thread Summary
The discussion revolves around calculating the standard deviation of values represented in a histogram bar, where ##n## is the number of events in the interval and ##k## is the range of possible measured values. There is confusion regarding whether the average value of ##k## can be equated to ##n## and how to interpret the variance in this context. Participants suggest that the measurements should be considered independent and question the definition of ##k## as a range, proposing it might represent the class width of the histogram bar. The overall consensus is that the wording of the problem is unclear, complicating the understanding of how to approach the calculation. Clarification on these points is sought to better tackle the problem.
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Homework Statement


If one bar of a histogram has been generated with ##n## entries from a total of ##x## measurements, i.e. the event occurs randomly ##n## times in the ##x## event interval, then what is the standard deviation of values in this bar? Let ##k## be the range of values that could have been measured for this particular bar of the histogram, and assume that the expectation value of ##k## is ##n##.

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The Attempt at a Solution


I'm finding the wording tricky to understand. ##n## is the number of events in the interval, and the average value of ##k## is also ##n##? The variance is the square of the distance from the mean and if all the events were equally likely, I'd divide by ##n## and have something like
##\frac{1}{n}\Sigma(k_i - n)^2##
But I'm not sure that's what it means when it says the event occurs randomly a total of ##n## times. I'd really appreciate any hints on how to tackle this, thanks for any help!
 
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It is strange to define k as a range. The range should be 0 to x.

I guess you have to assume that the x measurements are independent.
 
mfb said:
It is strange to define k as a range. The range should be 0 to x.

I guess you have to assume that the x measurements are independent.
Would you say then that ##k## is the class width of the single histogram bar being considered? That's how I've interpreted it. I also thought it would be quite a strange coincidence if the number of events ##n## recorded, which corresponds to the area of the bar, happened to be also the average value of ##k##. Which is what I take all the above to mean.

I think the wording is very confusing, but I've written it as it was given to us.
 
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