False precision (also called overprecision, fake precision, misplaced precision, excess precision, and spurious precision) occurs when numerical data are presented in a manner that implies better precision than is justified; since precision is a limit to accuracy (in the ISO definition of accuracy), this often leads to overconfidence in the accuracy, named precision bias.
In science and engineering, convention dictates that unless a margin of error is explicitly stated, the number of significant figures used in the presentation of data should be limited to what is warranted by the precision of those data. For example, if an instrument can be read to tenths of a unit of measurement, results of calculations using data obtained from that instrument can only be confidently stated to the tenths place, regardless of what the raw calculation returns or whether other data used in the calculation are more accurate. Even outside these disciplines, there is a tendency to assume that all the non-zero digits of a number are meaningful; thus, providing excessive figures may lead the viewer to expect better precision than exists.
However, in contrast, it is good practice to retain more significant figures than this in the intermediate stages of a calculation, in order to avoid accumulated .
False precision commonly arises when high-precision and low-precision data are combined, when using an electronic calculator, and in conversion of units.
If a car's speedometer indicates a speed of 60 mph, converting it to 96.56064 km/h makes it seem like the measurement was very precise, when in fact it was not. Assuming the speedometer is accurate to 1 mph, a more appropriate conversion is 97 km/h.
Measures that rely on statistical sampling, such as IQ tests, are often reported with false precision. Chapter 4. Much Ado about Practically Nothing
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