Generally, the error is calculated as the measure of the absolute difference to avoid the confusion of a negative error. Percent error is the absolute value of the error divided by the accepted value and multiplied by Sometimes, the Experimental value may be a smaller than the accepted value theoretical value , then the error obtained is negative.
If the experimental value is more than the accepted value, then the obtained error is positive. Often, the error is reported as the absolute value of the difference to avoid the confusion of a negative error.
Refer to the explanation. However, mass is always positive. If you are calculating percent error, the difference between the experimental value and the accepted value is an absolute value. So even if you get a negative number in your calculation, because it is an absolute value, it is positive. Note: Sometimes the experimental value is called the actual value, and the accepted value is called the theoretical value.
Notice that in the above formulas, absolute value bars are used to indicate that the difference between the two values is positive. Also notice that it doesn't matter which order the two values are in, because the difference is an absolute value.
When calculating percent error, what does it mean if I get a negative number for mass? Thus, in particular, a non-invariant function like. Whatever virtues it might have, it does not express a relative difference. The story does not end here. We might even find it fruitful to push the implications of invariance a little further. A neighborhood of this vertical line consists of lines with extremely large positive or extremely large negative slopes.
Any distance defined on the circle can therefore be used to define a relative difference. As an example of where this can lead, consider the usual Euclidean distance on the circle, whereby the distance between two points is the size of the angle between them. It is very debatable topic and many opensource contributors have discussed on the above topic. The most efficient approach till now is followed by the developers.
Please refer to this PR to know more. I was a bit confused on this for a while. In the end, its because if you are trying to measure relative error with respect to zero then you are trying to force something that simply does not exist.
For example, consider measuring error of gauge pressure the relative pressure from atmospheric vs absolute pressure. This is the proper application of relative error. The original application that used gauge pressure was more like "relative error of the relative value" which is a different thing than "relative error". You need to convert the gauge pressure to absolute before measuring the relative error.
The solution to your question is to make sure you are dealing with absolute values when measuring relative error, so that zero is not a possibility. Then you are actually getting relative error, and can use that as an uncertainty or a metric of your real percent error. If you must stick with relative values, than you should be using absolute error, because the relative percent error will change depending on your reference point.
It's hard to put a concrete definition on Feel free to nit pick, but zero essentially means nothing, it is not there.
This is why it does not make sense to use gauge pressure when calculating relative error. Gauge pressure, though useful, assumes there is nothing at atmospheric pressure. We know this is not the case though, because it has an absolute pressure of 1 atm. Thus, the relative error with respect to nothing, just does not exist, it's undefined. Feel free to argue against this, simply put: any quick fixes, such as adding one to the bottom value, are faulty and not accurate.
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