However, a bug tracking system is not an ongoing payment. The assigned values are correct or not; There is no (or should not) grey area. If codes, locations and degrees of gravity are defined effectively, there is only one attribute for each of these categories for a particular error. In this example, a repeatability assessment is used to illustrate the idea, and it also applies to reproducibility. The fact is that many samples are needed to detect differences in an analysis of the attribute, and if the number of samples is doubled from 50 to 100, the test does not become much more sensitive. Of course, the difference that needs to be identified depends on the situation and the level of risk that the analyst is prepared to bear in the decision, but the reality is that in 50 scenarios, it is difficult for an analyst to think that there is a statistical difference in the reproducibility of two examiners with match rates of 96 percent and 86 percent. With 100 scenarios, the analyst will not be able to see any difference between 96% and 88%. Once it is established that the bug tracking system is a system for measuring attributes, the next step is to examine the concepts of accuracy and accuracy that relate to the situation. First, it helps to understand that accuracy and precision are terms borrowed from the world of continuous (or variable) gags. For example, it is desirable that the speedometer in a car can carefully read the right speed over a range of speeds (z.B. 25 mph, 40 mph, 55 mph and 70 mph), regardless of the drive. The absence of distortion over a range of values over time can generally be described as accuracy (Bias can be considered wrong on average). The ability of different people to interpret and reconcile the same value of salary multiple times is called accuracy (and accuracy problems may be due to a payment problem, not necessarily to the people who use it).

Repeatability and reproducibility are components of accuracy in an analysis of the attribute measurement system, and it is advisable to first determine if there is a precision problem. This means that before designing an attribute contract analysis and selecting the appropriate scenarios, an analyst should urgently consider monitoring the database to determine if past events have been properly coded. First, the analyst should determine that there is indeed attribute data. One can assume that the assignment of a code – that is, the division of a code into a category – is a decision that characterizes the error with an attribute.