Procedures and Guidelines for Validating Contractor Test Data (2020) / Chapter Skim
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From page 73... ...
Proposed Practice for Validating Contractor Test Data 73 the Contractor's results and the SHA results. In either of these cases, the party whose paired t-test result yields the lowest p-value is the party whose results are considered validated.
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74 Procedures and Guidelines for Validating Contractor Test Data from samples 1-C, 3-C, and 6-C, and the Contractor's results from 2-C, 4-C, and 5-C will be used in the primary validation. Note A2 – In this example, the Contractor's and SHA's results from the same split sample are not used in the primary validation (F- and t-tests)
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Proposed Practice for Validating Contractor Test Data 75 Figure A.1 Sampling and Validation Process Using a Minimum of Six Contractor Results and Three SHA Results per Lot.
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76 Procedures and Guidelines for Validating Contractor Test Data A.1.4 Conduct an assessment of outliers among the SHA results and the Contractor results. A simple outlier detection procedure is provided in Annex B
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Proposed Practice for Validating Contractor Test Data 77 A.1.5.2 The F-critical value is obtained from an F table (Table C.2, C.3, C.4, or C.5 in Annex C) based on the degrees of freedom and the selected level of significance.
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78 Procedures and Guidelines for Validating Contractor Test Data A.1.5.9 If either the F-test or Welch's t-test indicates that the Contractor results and the SHA results are statistically different, then the Contractor's data are not validated by the primary assessment and the process moves into Secondary Validation. A.1.6 Secondary Validation - When the Contractor's data are not validated by the primary assessment, the next step is to compare SHA results and the Contractor results from the same samples (i.e., the split portions)
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Proposed Practice for Validating Contractor Test Data 79 A.1.7.1 The paired t-test statistic and critical values for the Referee - SHA pairs and the Referee - Contractor pairs are determined following the same steps described in A.1.6.1 and A.1.6.2. A.1.7.2 The three possible outcomes of the Dispute Resolution paired t-tests using Referee test results are: 1.
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80 Procedures and Guidelines for Validating Contractor Test Data For each lot, randomly take a minimum of four samples and split each of them into three equal portions. Label the samples 1-1-A, 1-1-C, 1-1-R, 1-2-A, 1-2-C, 1-2-R, etc.
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Proposed Practice for Validating Contractor Test Data 81 Figure A.2 Illustration of the Cumulative Validation Lot Approach
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82 Procedures and Guidelines for Validating Contractor Test Data A.2.3 When the SHA has completed testing of three consecutive lots, an outlier analysis is conducted on the three SHA results. Outlier detection is also conducted on the Contractor results from the same lots.
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Proposed Practice for Validating Contractor Test Data 83 Where is the number of samples corresponding to the larger variance, and is the number of samples corresponding to the smaller variance. A.2.4.4 When F-statistic F-critical, it is concluded that the variabilities of the Contractor data and SHA data are different.
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84 Procedures and Guidelines for Validating Contractor Test Data A.2.4.10 If either the F-test or Welch's t-test indicates that the Contractor results and the SHA results are statistically different, then the Contractor's data are not accepted by Primary Validation and the process moves into Secondary Validation. A.2.5 Secondary Validation - When the Contractor's data are not validated by the primary assessment, the next step is to compare SHA results and the Contractor results from the same samples (i.e., the split portions)
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