Experimental physics histogram problem

[Ertosthnes]

Homework Statement

You have run an experiment and generated a histogram. Suppose you had 853 counts in the bin centered at 1.60, and 2,439 counts in the bin centered at 1.85. If you were to repeat this experiment (by measuring the same source for the same time period, delta t) you know that you would measure a somewhat different number of counts in each of these two bins.

Estimate the experimental uncertainty in the measured number of counts for each of these two bins. In other words, estimate how much your measured number of counts (853 or 2,439) might differ from the true average number of counts in each bin.

Homework Equations

I don't know what the relevant equation is... I guess that's part of the problem.

The Attempt at a Solution

I don't know where to start with this, any help or advice you can give me is very welcome.

 

[Ertosthnes]

Solved it, never mind.

 

[thomate1]

I understand that experimental uncertainty is an inherent aspect of any measurement and it is important to quantify this uncertainty in order to accurately interpret the results of an experiment. In this case, the uncertainty in the measured number of counts for each bin can be estimated using statistical methods.

One approach is to calculate the standard error of the mean, which is a measure of the variation of the data around the true average. This can be calculated using the formula:

Standard error = standard deviation / √(n)

Where n is the number of measurements. In this case, n would be the number of times the experiment is repeated, which is not specified in the homework statement. However, assuming that the experiment is repeated multiple times, the standard error can be used to estimate the uncertainty in the measured number of counts.

Another approach is to use confidence intervals, which provide a range of values within which the true average is likely to fall. The width of the confidence interval can be used as an estimate of the uncertainty in the measurement.

It is also important to consider any sources of systematic error in the experiment, which can affect the accuracy of the measurements. These can be identified and minimized through careful experimental design and control.

In summary, the uncertainty in the measured number of counts for each bin can be estimated using statistical methods such as standard error or confidence intervals, taking into account both random and systematic errors in the experiment.