Forest Mensuration. Brack and Wood
Index Overview Help Types of error Describing error Error calculations |
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the difference between the measured value and the true value.It is important for anyone involved in measurement to have a general knowledge of likely error sources, so that:
Errors arise from many sources. It pays the natural resource manager or scientist to determine as early as possible what are likely to be the dominant sources of error in the measurement task and to devote sufficient time to devising ways of reducing these errors. This is best accomplished by a preliminary trial - in short, a rehearsal. As well as providing a provisional estimate of the size of the various errors, the rehearsal enables one to check that the procedures are appropriate and sound.
There are four kinds of error:
Accidental error can be reduced by using more accurate and precise equipment but this can be expensive. A competent scientist is expected to be able to assess in advance how good an instrument needs to be in order to give results of an accuracy sufficient for the task in hand. In other words, he / she is expected to make an appropriate choice from the equipment available (or to design a more appropriate instrument).
To avoid bias being introduced via faulty instruments, it is essential to check all instruments before one commences any important measuring project and re-check periodically during the course of the project.
Mistake
Mistakes are caused by human carelessness, casualness or fallibility, e.g. incorrect use or reading of an instrument, error in recording, arithmetic error in calculations. There is no excuse for mistakes, but we all make them! In general, never be satisfied with a single reading no matter what you are measuring. Repeat the measurement. This shows up careless mistakes and improves the precision of the final result.
Accidental error
Accidental errors are unavoidable. They arise due to inconstant environmental conditions, limitations or deficiencies of instruments, assumptions and methods. Accidental error is usually not important as the error tends to be compensating.Bias
Bias is a systematic distortion in a measurement, i.e. it is a non-compensating error. Common sources of bias are:
The only practical way to minimise measurement bias is by:
Complete elimination of bias may be costly. One may have to compromise in which case one should recognize that bias is present and appreciate its effects. Sampling error
Sampling error is the error associated with an estimate purely due to sampling.
Note: there is little sense in taking measurements in the field to a precision greater than needed for their ultimate use. Conversely, the precision of field measurements should not be less than that required for later computations.
http://online.anu.edu.au/Forestry/mensuration/ERROR.HTMDescribing errors
Two terms are closely related to error, viz. accuracy and precision:
the closeness of a measurement or estimate to the true value
More broadly, accuracy is the degree to which a statement or quantitative result approaches the truth. Accuracy refers to the size of the total error and this includes the effects of biases. An estimated value may be inaccurate because of one or more kinds of error.
Error calculations
There are three fundamental theorems in determining errors. Anyone involved in measurement should be familiar with them.
The measure of the random errors that affect precision is the statistical parameter standard error. The smaller the standard error of an estimate, the more precise is that estimate.
a = sqrt(b^2 + c^2)
a/A = sqrt([b/B]^2 + [c/C]^2)
a/A = n x c / C
where
^n denotes raising to the power of n,
and sqrt(Y) denotes taking the square root of Y
Cris.Brack@anu.edu.au
Sun, 11 May 1997