Precision, like accuracy, is an inherent attribute of the results of water quality monitoring and analysis, and it should be achieved correctly according to the characteristics of the methods used. Precision The precision characterization of monitoring data is the degree of agreement between measured values obtained from repeated analysis of a homogeneous sample under controlled conditions using a specific analytical procedure. It reflects the size of the random error in the analysis method or measurement system. The smaller the random error of the test result, the higher the precision of the measurement. Precision is usually expressed in terms of range, mean deviation and relative mean deviation, standard deviation and relative standard deviation. Standard deviation is an unbiased measurement and is often used in mathematical statistics.

So What Do You Need to Pay Attention to in Testing Precision? It Can Be Divided Into the Following Points

1.The precision of the analysis results is related to the concentration level of the substance to be measured in the sample, so if necessary, two or more samples of different concentration levels should be taken to check the precision of the analysis method;

2.Precision can vary due to changes in experimental conditions related to the measurement, usually the precision obtained from a whole batch of analysis results is often higher than the precision of the results scattered over a longer period of time, if possible, it is best to divide the fixed sample into several batches scattered over an appropriate long period of time for analysis;

3.The reliability of the standard deviation is affected by the number of measurements, so a good estimate of the standard deviation (such as determining the precision of a certain method) requires a sufficient number of measurements;

4.The precision of the method is usually understood by analyzing standard solutions, which may be different from the precision of analyzing actual samples;

5.The data with good accuracy must have good precision, and the data with poor precision is difficult to determine its accuracy.

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