Abstract This practice covers the required correction procedures for examining sequential control tire data for any systematic or bias (not random) variation due to changing test conditions that may influence absolute and also comparative performance of candidate tires, as they are tested over any short or extended time period. The procedures provided here may be used for any repetitive tire traction testing in any environment (for example, dry, wet, snow, ice) where test conditions are subject to change. This practice does not address the issue of rejecting outlier data points or test values that might occur among a set of otherwise acceptable data values obtained under identical test conditions in a short time period. Method A uses the initial operational conditions defined by the first control traction test as a reference point. The calculations correct all traction test performance parameters (for example, traction coefficients) to the initial level or condition of the pavement or other testing conditions, or both. With this method, corrections may be made after only a few candidate and control sets have been evaluated. Method B uses essentially the midpoint of any evaluation program, with the grand average traction test value as a reference point. This grand average value is obtained with higher precision than the initial control traction test average of Method A because it contains more values. However, Method B corrections cannot be made until the grand average value is established, which is normally at the end of any program.Scope 1.1 This practice covers the required procedures for examining sequential control tire data for any variation due to changing test conditions. Such variations may influence absolute and also comparative performance of candidate tires, as they are tested over any short or extended time period. The variations addressed in this practice are systematic or bias variations and not random variations. See Appendix X1 for additional details. 1.1.1 Two types of variation may occur: time or test sequence “trend variations,” either linear or curvilinear, and the less common transient or abrupt shift variations. If any observed variations are declared to be statistically significant, the calculation procedures are given to correct for the influence of these variations. This approach is addressed in Method A. 1.2 In some testing programs, a policy is adopted to correct all candidate traction test data values without the application of a statistical routine to determine if a significant trend or shift is observed. This option is part of this practice and is addressed in Method B. 1.3 The issue of rejecting outlier data points or test values that might occur among a set of otherwise acceptable data values obtained under identical test conditions in a short time period is not part of this practice. Specific test method or other outlier rejection standards that address this issue may be used on the individual data sets prior to applying this practice and its procedures. 1.4 Although this practice applies to various types of tire traction testing (for example, dry, wet, snow, ice), the procedures as given in this practice may be used for any repetitive tire testing in an environment where test conditions are subject to change. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use. 1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
