So what is the temperature resolution?
In this case, use statistical analysis, given a % confidence we want to achieve of correctly
being able to distinguish two different temperatures. If the distribution is assumed to be
Gaussian, we can use a multitude of test to determine the resolution (students t-test is
easy).
Precision- is the number of distinguishable alternatives from which the result is selected.
In signals that have been A/D converted, this can be no more than 2^ # bits in the
converter.
Range = resolution * precision
Ex. A digital thermometer
Range: 0 to 99.9°C
Display is 3 digits XX.X, so assume resolution is 0.1 °C
Precision is 1000, or about 10 bits
Please note: Webster has another definition of precision (the quality of obtaining the
same output from repeated measurement of the same input). The word “precision” can be
used in both cases. In this class, I am most concerned with distinguishable alternatives.
Reproducibility- is the ability to give the same output for equal inputs over some period
of time (full range or standard deviation).
Specificity- is the ability of an instrument to respond to the desired input only. Signal-tonoise
ratio is one measure. The number of false positives in a binary system is another.
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