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The objective of measurement is to provide data on the amount of interest in the measurement. But there is no exact measurement. When the quantity is measured, the result depends on the measurement system, the measurement procedure, operator skill, the environment, and other influences. Even if the quantity is measured several times, in the same way, and under the same conditions, a different value is usually obtained, measured each time, assuming that the measurement system contains sufficient accuracy to distinguish the values.

Whenever something measured, it compared against a stander and there always a chance for an error. Errors can be categories to two types:
1-Random errors and those are unpredictable errors brought about by things usually out of control such as electrical noise affecting an ammeter reading.
2-Systematic errors and this sort of error happen due to measuring equipment like a Vernier caliper that does not read zero when it should.

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When scientists measure or calculate their data, they usually assume that some real or ‘true value’exist based on how to determine what is measured (or calculated). Scientists who report their results usually identify a set of values that expect this “real value” to occur. The most popular method to determine the scale of values is:
Measurement = best estimate ± uncertainty
Example: Measuring 2.61 cm ± 0.01 cm means that the experimenter is confident that the actual value of the quantity measured is between 2.60 g and 2.62 g. Uncertainty best appreciated for the experimenter for how much experimental quantity may be of “real value.”.

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