In all experimental measurements, there is a degree of uncertainty.
This is usually dependent on:
The limitation of the measuring instrument. (section
1.5.1)
The skill of the person making the measurement.
The instruments' built-in or inherent errors are called systematic
errors. If a scale is not calibrated corrected, it would yield a reading
that is consistently too high or too low. When errors are introduced by the
skill or ability to read the scientific instruments, this will lead to results
that may be either to high or too low. These are called random
errors.
Although all experimental measurements are subject to error, we
can still trust our measurements in terms of their precision
and accuracy.
Precision indicates the reproducibility
of a measurement. That is, the closeness in agreement among the values when
the same quantity is measured several times. If the series of measurements is
reproducible, then good precision is obtained as careful inspection of each
measurements deviates only by a small amount from the average of the series.
On the other hand, if there is a wide deviation among the series of measurements
the precision is poor. A measurement is said to be accurate
if it is close to the known "accepted" or "most
probable" value.
For example, the boiling point of pure water at sea level is 100oC.
Using the same thermometer in four trials of measurements, the data collected
is as follows:
Boiling point of pure water at sea level
96.9oC
96.8oC
97.1oC
97.0oC
Since these figures show a high reproducibility, the measurements
are precise. However, the values are considerably
off from the accepted value of 100oC.
So, the measurements are not accurate. In this
set of measurements, we probably would suspect that the inaccuracy arises from
a mis-calibrated thermometer.