No measurement is exact. When a quantity is measured, the outcome depends on the measuring system, the measurement procedure, the skill of the operator, the environment, and other effects. Even if the quantity were to be measured several times, in the same way and in the same circumstances, a different measured value would in general be obtained each time, assuming that the measuring system has sufficient resolution to distinguish between the values. The dispersion of the measured values would relate to how well the measurement is made. Their average would provide an estimate of the true value of the quantity that generally would be more reliable than an individual measured value. The dispersion and the number of measured values would provide information relating to the average value as an estimate of the true value. However, this information would not generally be adequate.
There are three types of errors which must be considered
- Spurious errors (human mistakes and instrument malfunctions).
- Random errors (experimental and reading errors).
- Systematic errors (which may be either constant or variable).
Spurious errors are errors which invalidate a measurement. They are like outliers. They cannot be incorporated into a statistical analysis. Random errors are errors that affect the reproducibility of measurement. The mean random error of a summarized discharge over a period is expected to decrease when the number of discharge measurements during the period increases. Mean random error approaches zero over a long period of measurement. Systematic errors are errors which cannot be reduced by increasing the number of measurements. Whenever there is an evidence of a systematic error of a known sign, the mean error should be added or subtracted from the measured results.
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