The types of errors can be divided into systematic errors, accidental errors and negligent errors according to their characteristics.
aerometer The types of errors can be divided into systematic errors, accidental errors and negligent errors according to their characteristics.
First, systematic error
Systematic error refers to the error caused by undetected or unconfirmed factors in the measurement. The cause of system error is generally believed to be due to poor instruments, such as inaccurate scale, uncorrected weights, changes in the test environment, such as changes in temperature, pressure, humidity, etc. Systematic errors can be eliminated by correcting instruments, controlling the environment, and correcting bad habits.
Second, accidental error
Accidental error means that under the condition that systematic error has been eliminated, but the measured data is still different in the last or last two digits, then this error is called accidental error. The characteristics of accidental error are large when small, positive when negative, the direction is not necessarily. The causes of accidental errors are not clear and therefore cannot be controlled. However, if the same precision gas meter is used, under the same conditions, the same physical quantity is measured many times, if the number of measurements is enough, it can be found that the accidental error completely obees the statistical law, and the arithmetic average of the accidental error will gradually approach zero. Accidental errors can be treated with error theory.
Three, fault error
Fault error, also known as gross error, is caused by human factors, such as careless operators, excessive fatigue or incorrect operation and other factors. The way to eliminate errors is to improve the staff's sense of responsibility, improve the working system, and strengthen the audit of data. Due to the existence of gross error, the discreteness of the measured data is relatively large. First of all, we should check the data from the test and collection, and eliminate the data with significant errors.
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