How do I account for measurement uncertainties in temperature data analysis?

In summary, the speaker has taken five temperature measurements every 10 meters over a distance of 100m. They have calculated the mean value, standard deviation, and standard error for each dataset of N=5. They have represented this data in Excel with error bars, with mean temperature on the y-axis and distance on the x-axis. The speaker is now questioning how to incorporate the accuracy of their measurement equipment, which is specified as +/- 5% and +/-3 digits. They have requested for the thread to be moved to a more appropriate forum for better visibility.
  • #1
gnurf
370
8
In an attempt to determine how the temperature varies over a distance of 100m I have taken five temperature measurements for every 10 meters, for a total of 55 measurements. I have then, for each dataset of N=5, calculated the mean value, standard deviation and standard error. Finally, I've plottet the mean value with error bars in Excel in what I believe is the most accurate and informative way to represent this data (mean temperature on the y-axis, and distance on the x-axis).

So far so good I think, but how do I include the accuracy of the, say, 3 1/2 digit measurement equipment if it was specified as accurate to within +/- 5% and +/-3 digits?
 
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  • #2
Moderator(s): I'm moving this to a less obscure subforum (EE probably) in order to get some more traffic. It was misplaced in the first place I think. Please close or delete this thread.
 

Related to How do I account for measurement uncertainties in temperature data analysis?

What is a measurement uncertainty?

A measurement uncertainty is the amount of doubt or error associated with a specific measurement. It reflects the range of values within which the true value of a measurement is likely to lie.

What factors contribute to measurement uncertainties?

Several factors can contribute to measurement uncertainties, such as the precision of the measurement instrument, variations in environmental conditions, human error, and limitations in the measurement process.

How is measurement uncertainty calculated?

Measurement uncertainty is calculated by considering the combined effects of all the contributing factors. This can be done through statistical analysis or by using mathematical formulas that take into account the individual uncertainties of each factor.

Why is it important to consider measurement uncertainties?

Measurement uncertainties are important because they provide a measure of the reliability and accuracy of a measurement. They also help to identify potential sources of error and guide improvements in the measurement process.

How can measurement uncertainties be minimized?

Measurement uncertainties can be minimized by using more precise instruments, controlling environmental variables, following standardized measurement procedures, and regularly calibrating equipment. It is also important to properly document and analyze the data to identify and address any sources of error.

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