Errors can be either systematic or random.
A systematic error involves a bias of some kind.
For example, a medical scale improperly set such that an empty platform
weights 1.1 kg will yield measurements that are consistently 1.1 kg more than
the true weights of individuals who use that scale.
Measuring devices used in commerce (for example: supermarket scales use
to weight meat and produce and gasoline pumps) are checked and certified
accurate by local government officials to protect consumers.
A gasoline pump that delivers 5% less gas than indicated cheats the
customer out of one gallon for every twenty one gallons purchased.
Random errors involve scatter.
A baker producing bread listed as twenty ounces per loaf has difficulty
making each loaf such that it weights precisely twenty ounces.
Some loaves are a little bit heavier, some might be a little bit lighter.
If loaves sold customers average twenty ounces in weight, on a given day
one family might get less bread for their money than another family.
However, if the variations in weight are truly random and there is no
effort made to select heavy loaves, customers are not at a disadvantage because
loaves that are too light are balanced out by loaves that are too heavy.
However, systematic error might also occur at the bakery.
A baker setting out to cheat customers might modify his recipe such that
only the heaviest loaves weight twenty ounces, while a baker concerned with
legal or public relations consequences of selling underweight bread might see to
it that all loaves weigh over twenty ounces.
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