ISO 英文 – INTERNATIONAL STANDARD IS0 TECHNICAL CORRIGENDUM 1 Published ISO Accuracy (Trueness and Precision) of Measurement Methods and Results – Part 5: Alternative Methods for the Determination of the Precision of a. Find the most up-to-date version of ISO at Engineering
|Published (Last):||6 July 2018|
|PDF File Size:||7.95 Mb|
|ePub File Size:||20.13 Mb|
|Price:||Free* [*Free Regsitration Required]|
Excluding outliers can sometimes have a large effect on the estimates of repeatability and reproducibility standard deviations, but in practice, when applying the outlier tests, the data analyst may have to use judgement to decide which data to exclude. There are robust methods that combine test results within cells in a robust manner, and they would be more complicated to apply in practice.
The decision as to whether to use robust methods or methods that require outliers to be discarded should be made by the statistical expert, and reported to the panel.
In the same figure, Laboratories 8 and 9 gave h statistics that are nearly ixo positive, indicating consistent positive biases in their data but smaller than the negative bias in Laboratory 5.
Consider the results of the outlier tests in Example 1 of 4. Figure 2 does not reveal any noteworthy pattern. NOTES 1 It may 5725–5 of interest to perform a significance test to see if the variation between samples is statistically significant, however, this is not a necessary part of the analysis.
The robust methods described here do not replace these cell averages, standard deviations or ranges or differences, but provide alternative ways of combining them to obtain the statistics that are used to calculate the repeatability and reproducibility standard deviations.
If a laboratory is reporting generally biased results, then most of the h statistics for the laboratory, in the graph derived from the cell averages, will be large and in the same direction.
The analysis would then continue with an investigation of possible functional relationships between the repeatability and reproducibility standard deviations and the general average. E The repeatability standard aviation srj, between-samples standard deviation sW, between-laboratory standard deviation sLp and reproducibility standard deviation sR using: This part of IS0 complements IS0 by providing alternative designs that may be ios more value in some situations than the basic design given in IS0and by providing a robust method of analysis that gives estimates of the repeatability and reproducibility standard deviations that are less dependent on the data analyst’s judgement than those given by the methods described in IS0 When the material is a natural or manufactured product, it can be difficult to find two products that are oso similar for the purposes of a split-level experiment: A design for a heterogeneous material This is useful when it is possible to investigate the causes of the largest laboratory biases with the aim of taking corrective action.
An experiment on a heterogeneous material 5.
Graphs of this type give an easily understood picture of the amount of variation arising from the different sources between test results, between samples, and between laboratories. It is reasonable to assume that the variation between samples is random, does not depend on the laboratory, but may depend on the level of the experiment, so the term Hiil has a zero expectation, and a variance: Precision refers to the closeness of agreement between test results.
The general average with summation over irand k: This requirement may be written: Applying Algorithm 5725- to the cell averages gives the results shown in table 26,where now the cell averages have been sorted into increasing order.
An experiment on a heterogeneous material I S 0 Robust analysis for a particular level of an experiment on a heterogeneous material 6.
Level 5 in that example is of particular interest because Laboratory 1 gave a cell average that was shown to be a near-straggler by Grubbs’ test, and Laboratory 6 gave a cell range that was shown to be a nearstraggler by Cochran’s test.
These tests again indicate that the data from Laboratory 5 are suspect. Your Alert Profile lists the documents that will be monitored. Figure 4 shows that, in this experiment, at Level 6, there is wide variation between the cell averages, so that, if the test method were to be used in a specification, it is likely that disputes would arise between vendors and purchasers because of differences in their results.
To test for stragglers and outliers in the cell averages, apply Grubbs’ tests to the values in each column of table 3 in turn. Laboratory 5 gives a point in the bottom left-hand corner of the graph, and Laboratory 1 gives a point in the top right-hand corner: Your basket is empty.
Figure 7 shows consistent positive or negative h statistics in most laboratories with Laboratories 1, 6 and 10 again achieving the largest values. Calculation of the sum of squares for repeatability 6 Robust methods for data analysis 6.
BS ISO 5725-5:1998
The corresponding formulae for the split-level experiment are set 55725-5 below. If it is necessary to reduce this uncertainty, the uniform-level design should be used instead.
An example is given in figure 1. Usually, data shown to be outliers are excluded from the calculations, and data shown to be stragglers are included, unless there is a good reason for doing otherwise. Robust methods for data analysis Iao organization, management and quality. Using equation 79 in 6.
ISO Accuracy of Measurement Methods and Results Package
However, the above equation may be derived 5725–5 replacing p in equation 9 of IS0 An application of the general formulae 5. Reference number IS0 IS0 consists of the following parts, under the general title Accuracy trueness and precision of measurement methods and results: Worldwide Standards We can source any standard from anywhere in the world.
This is the approach that is used in the examples that follow.