Measuring Errors of Factors and Responses

An important property of design of experiments is a search for increased accuracy in fixing a factor and measuring an error. The researcher must be able to determine and estimate a measurement error correctly. Measurements and measurement errors are a subject of special study, see [7, 8]. 

Measurement should not be brought down to simply determining a measured value but also to estimating errors in measurements, called the measurement error. There are several kinds of errors in measurement robust, systematic and random. 

Robust errors result from disrupting basic conditions for measuring, researcher s error, etc. A researcher is asked to check the probability of appearance of a robust error. A robust error appears as a measured value that is drastically different from others. This error may be avoided if another researcher who is ignorant of former measurements repeats it. The same effect may be achieved when the same researcher repeats measurements after some time when he has already forgotten the results the of first ones. Such a result has to be rejected if a robust error has been discovered. 

Variance value or variance measurement is in this case also determined by the well-known formula  

The positive value from the variance measurement root square is called the error mean square or standard error. 

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