Uncertainty in Mean Value: How Many Decimal Places?

In summary, the conversation discusses determining the appropriate number of decimal places to use when calculating the mean value of a set of measurements. It is suggested that using only one decimal place is appropriate, as using none would be uncertain and using more than one would be pointless. It is also discussed that the standard deviation may play a role in determining the number of decimal places, and a formula is mentioned for calculating the maximum error in a standard-normal distribution. There is some confusion about where to draw the line for including additional decimal places, with the suggestion that if the standard error is less than 0.1, one can add one more decimal place, and if it is less than 0.01, another decimal place can be added.
  • #1
Gavroy
235
0
hi

i have some measured values that refer to a simple experiment where a stone was thrown along a fixed length and now i have these values for the time the stone needed

time 13.8 13.7 13.9 13.5 14.4 14.6 14.1 14.3 13.9 14.7

i was asked to explain how many decimal places one would write down when one determines the mean value of this set?

well, i guess it is only one, as none would be pretty uncertain and more than one would be pointless.
but then i was also asked, how many values i would need(these are 10) in order to be able to write down another decimal place and also how many values i would need to write down a third decimal place and so on. is there any rule or does anybody here have an idea what an appropriate number might be?
 
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  • #2
Propagnation of uncertainty? maybe it is a purely statistical question so:
Another consideration is the standard deviation i get: [itex]\sigma = 0.4[/itex]
So maybe you need to specify 0 decimals because of the SD, but it can be calculated more precisly:
You need to assume that the time measurements follows a distribution, maybe normal-dist.?
The max error E in a Standard-normal distribution is given by:
[itex] E = z_{\alpha/2}\dfrac{\sigma}{\sqrt{n}}[/itex]
where n is the number of measurements and alpha is the significance(by standard 5%).
 
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  • #3
sorry, that i maybe misunderstand you, but are you saying that if the standard error is less than 0.1 one can write down the mean value with one more decimal place and if it is less than 0.01 one can write down another decimal place? or where would you draw the line?
 

Related to Uncertainty in Mean Value: How Many Decimal Places?

1. What is propagation of uncertainty?

Propagation of uncertainty is a method used to estimate the uncertainty or error in a calculated value based on the uncertainties in the measured values used to calculate it. It takes into account the variations and errors in the input variables to determine the overall uncertainty in the final result.

2. Why is propagation of uncertainty important?

Propagation of uncertainty is important because it allows us to understand and communicate the level of uncertainty in a calculated value. This is crucial in scientific research and decision making, as it helps us make informed conclusions and assess the reliability of our results.

3. What are the sources of uncertainty in propagation of uncertainty?

The sources of uncertainty in propagation of uncertainty can include measurement errors, instrument limitations, inaccuracies in data, and assumptions made during calculations. Other factors such as environmental conditions and human error can also contribute to uncertainty.

4. How is propagation of uncertainty calculated?

Propagation of uncertainty is typically calculated using mathematical equations that take into account the uncertainties in the input variables. One common method is the "sum of squares" method, where the individual uncertainties are squared and then added together to determine the overall uncertainty in the final result.

5. Can propagation of uncertainty be reduced or eliminated?

Propagation of uncertainty cannot be completely eliminated, as there will always be some level of uncertainty in any measurement or calculation. However, it can be reduced by improving the accuracy and precision of measurements, using more precise instruments, and minimizing potential sources of error.

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