Can More Readings Reduce Fractional Error in Measurement?

AI Thread Summary
Fractional uncertainty is not influenced by systematic error because systematic errors are consistent and predictable, allowing for potential adjustments to measurements. In contrast, random errors are unpredictable and cannot be corrected. Taking multiple readings and averaging them can help reduce random error but will not mitigate systematic error, as it will consistently skew the results in the same direction. Therefore, while averaging may improve precision in the presence of random errors, it does not address the issue of systematic errors. Understanding the distinction between these types of errors is crucial for accurate measurement.
Angela Liang
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Why is fractional uncertainty not affected by systematic error? For example à vernier calipers measures the diameter of a coin:
(5.06+-0.04) mm
Can taking more readings, say 6, and taking average, reduce fractional error?
 
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I'm not exactly sure about your terms, but here is my two cents:
A systemic error may be very consistent and predictable. That makes it conceivable to determine the error and make adjustments to the measured value and get the true value. On the other hand, a truly random error is difficult to determine and you can not make adjustments to the measured value.

A systemic error may just repeat the same error over and over, so taking the average of multiple readings will not reduce the error.
 
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FactChecker said:
I'm not exactly sure about your terms, but here is my two cents:
A systemic error may be very consistent and predictable. That makes it conceivable to determine the error and make adjustments to the measured value and get the true value. On the other hand, a truly random error is difficult to determine and you can not make adjustments to the measured value.

A systemic error may just repeat the same error over and over, so taking the average of multiple readings will not reduce the error.
Thanks!
 
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