Reducing Uncertainty in an Experiment to 0.012 s

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To reduce the uncertainty of an experiment from 0.03 s to 0.012 s, increasing the number of measurements is essential. The ratio of the current uncertainty to the desired uncertainty (0.03/0.012) suggests that approximately 18 measurements are needed, based on the initial 7 measurements taken. Identifying and improving the measurement that introduces the most error is crucial for achieving this goal. Additionally, using more precise timing methods, such as a laser sensor, can help minimize initial error and enhance overall accuracy. Implementing these strategies will effectively lower the uncertainty in the experiment.
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Homework Statement


I want to lower the uncertainty of an experiment to 0.012 s from 0.03 s by performing x number of more measurements. I already have the mean, std dev, variance.

I know I need the factor of 0.012/0.03 somehow but I don't know where to apply it.
Any suggestions?
 
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Identify the measurement that introduces the most amount of error and explore a way for improving that. I think it does little good to reduce uncertainty of quantities you already know with sufficient precision.
 
That's not really what i was asking...
So say I already took N=7 measurements and have the best estimated uncertainty for the mean time, which is 0.03.
Now I want to reduce that number to 0.012 by taking some new number of measurements.
Wouldn't I just use the ratio 0.03/0.012 = 2.5 and then multiply that by 7?
So I would need to take 17.5, or 18, measurements to reduce my uncertainty to 0.012...?
 
If it is something like timing something, then yes you can increase the number of oscillations say linearly as you suggest.

If your original modeling for the error took 200 ms as your stop watch reaction time and you want to achieve a 12 ms error, then figure that 17 oscillations will afford you that precision.

However you can also consider getting a laser sensor that attacks the problem with the notion that the error introduced is smaller to begin with.
 
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