Finding the random uncertainty of a set of values

In summary, the LED switch-on voltage is 1.45, 1.46, 1.46, 1.44, and 1.45 volts. The mean of these readings is 1.45 volts and the random uncertainty is +/-0.004 volts.
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123leo
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Ok, for the switch-on voltage of a red LED I have the readings as follows, all in volts: 1.45, 1.46, 1.46, 1.44, 1.45. The mean of these readings, in volts, is 1.45 (I rounded up to 2 decimal places as my scale reading uncertainty was +/-0.01V, and my teacher told me to round them up since to state my scale reading uncertainty for the mean the mean will have to have the same number of decimal places as the scale reading uncertainty). Now, my random uncertainty for these values is +/-0.004V, which is not to 2 decimal places (it's to 1 significant figure). So, I was wondering if I would have to make my random uncertainty have 3 significant figures (+/-0.00400V?) to express the random uncertainty in absolute form (Mean Value+/-Random Uncertainty). And if I did so, would it be, in terms of physics, correct?
 
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To get the uncertainty in one measurement, we need to know the uncertainty in the mean, x .
We expect that because the mean takes into account multiple measurements, its uncertainty will be less than that for a single measurement Indeed this is so.
The standard deviation of the mean, or standard error, is defined as: Sigma(x bar) = sigma (x)/ sqrt (N)

where N is the number of measurements of the quantity x.
The standard deviation of the mean is related to the uncertainty in one measurement, but is reduced because multiple measurements have been taken.
It is easy to see that the more trials performed in an experiment, the smaller the uncertainty will be.

Then for a series of measurements of one quantity x with independent and random errors, the best estimate and uncertainty can be expressed as: (value of x) = x(besT) +/- Sigma(xbar)

i think you should visit the following for details
<http://web.mit.edu/fluids-modules/www/exper_techniques/3.Statistical_Anal._of_Unce.pdf>
 
  • #3
Looking at the figures, .004 has all the significance that is possible for these data.
 
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1. What is random uncertainty?

Random uncertainty refers to the inherent variability or unpredictability in a measurement or set of values. It is also known as "experimental error" and can be caused by a variety of factors, such as equipment limitations, human error, or natural variation in the data.

2. How is random uncertainty different from systematic uncertainty?

While random uncertainty is caused by inherent variability, systematic uncertainty is caused by a consistent error or bias in the measurement process. This means that systematic uncertainty can be corrected for or reduced, while random uncertainty is unavoidable.

3. How is random uncertainty calculated?

To calculate random uncertainty, the standard deviation of the data set is typically used. This measures the spread or variability of the values from the mean. The larger the standard deviation, the greater the random uncertainty in the data.

4. Can random uncertainty be eliminated?

No, random uncertainty cannot be completely eliminated. However, it can be reduced by taking multiple measurements and calculating an average, which can help to minimize the effects of random errors.

5. How does random uncertainty affect the reliability of my results?

Random uncertainty can affect the reliability of your results by making them less precise. This means that the true value of the measurement may fall within a range of values rather than being a specific number. However, with careful measurement techniques and multiple trials, the impact of random uncertainty can be minimized and the results can still be considered reliable.

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