Basic knowledge of data processing for testing instruments (1)

Simple introduction error and related concepts of the basic knowledge of instrument data processing → true value and standard value
The error is the difference between the measured value and the real result. To know the magnitude of the error, you must know the true result. This real value is called the "true value".
Real value
In theory, the content of a component in a sample must have an objectively existing true value, called "true value" or "true value." It is represented by "μ". But in fact, for the true value of objective existence, people can not know precisely, and can only gradually approach the true value with the continuous improvement of measurement technology. In actual work, “standard value” is often used instead of “true value”.
2. Standard value
The use of a variety of reliable analytical methods, the average of the results of repeated measurements by experienced analysts, is a more accurate result.
In practice, standard values ​​are generally used instead of true values. For example, the atomic weight and the physicochemical constant: the Afogadro constant is 6.02×10.
Related to our experiments is the theoretical content of the elements in the pure substance as the true value.
Accuracy
Accuracy is the degree to which the measured value is close to the true value.
In order to obtain reliable results, in actual work, people always measure several times under the same conditions, and then average them as measured values. These measurements under the same conditions are generally referred to as parallel determinations. If these data are close to each other, the precision of the analysis is high.
2. Precision
Precision is the degree to which several parallel measurements are close to each other.
3. Relationship between precision and accuracy
(1) Precision is a prerequisite for ensuring accuracy.
(2) High precision does not necessarily guarantee high accuracy.

Error
(1) Definition: The difference between the individual measurement results X, X ... X and the true value μ is called the error of the individual measurement, referred to as the error.
(2) indicates that the error of each measurement result is represented by X - μ, X - μ ... X - μ, respectively.
(3) Calculation method:
Absolute error
Relative error
For absolute error - the measured value is greater than the true value, the error is positive; the measured value is less than the true value, and the error is negative.
For the relative error - the percentage of the reflection error in the measurement results is more practical.
2. Deviation
Deviation is the measure of precision.
Classification of errors → systematic error
1. Definition
Errors caused by a fixed cause, if you can find out the cause and try to measure it, can be eliminated, so it is also called measurable error.
2. Features
It has unidirectionality, testability and repeatability. That is: positive and negative, the size has a certain regularity, repeated in the repeated measurements.
3. Cause
(1) Method error: The error caused by the analysis method itself. The method error is due to the inadequacy of an analytical method itself. As the analysis progresses, the effects of interfering ions are not eliminated.
(2) Operational error: due to subjective reasons of the operator. For example, when titration analysis, each person has different sensitivity to the color change of the end point of the titration, and different people have different judgments on the end point.
(3) Instrument and reagent error: The instrument error comes from the instrument itself is not accurate enough. For example, the balance arms are not equal in length, and the weight changes after long-term use. The reagent error is derived from the impure reagent.
Note: Systematic errors occur repeatedly in a fixed form, and increasing the number of parallel measurements cannot be eliminated.

Classification of errors → random error
Random errors are caused by accidental factors that are difficult to control and cannot be avoided. Also called accidental error.
1. Features
The size, positive and negative are not fixed and cannot be reduced or eliminated by calibration. It can be reduced by increasing the number of measurements.
2. Cause
Temperature changes, humidity changes, and even dust during operation can cause fluctuations in measurement results.
The systematic error and the random error division are not absolute. The difference in the judgment of the titration end point has personal subjective reasons and contingency. Random errors are more contingent than systematic errors. The “fault” in the analysis work is different from the two errors. It is an error caused by the analyst's carelessness or violation of the operating procedures.
Http://news.chinawj.com.cn Editor: (Hardware Business Network Information Center) http://news.chinawj.com.cn

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