5.1 This practice should be used whenever measured color-scale or color-difference-scale values are to be compared to an established tolerance. In this way it can be demonstrated quantitatively that the sampling and measurement procedures are adequate to allow an unambiguous decision as to whether or not the mean results are within tolerance.

5.2 This practice is based on portions of SAE J 1545, as it applies to painted or plastic automotive parts. It is generally applicable to object colors in various materials. Textured materials, such as textiles, may require special consideration (see SAE J 1545 and STP 15D Manual on Presentation of Data and Control Chart Analysis5).

5.3 While Practice E178 deals with outliers, it does not include definitions relating to the box and whisker technique. The definition of an outlier is operational and a little vague because there is still considerable disagreement about what constitutes an outlier. In any normally distributed population, there will be members that range from minus to plus infinity. Theoretically, one should include any member of the population in any sample based on estimates of the population parameters. Practically, including a member that is found far from the mean within a small sample, most members of which are found near the mean, will introduce a systematic bias into the estimate of the population parameters (mean, standard deviation, standard error). Such a bias is in direct contrast with the goal of this practice, namely, to reduce the effects of variability of measurement. For the purposes of this practice, no distinction is made between errors of sampling and members of the tails of the distribution. Practice E178 has several methods and significance tables to attempt to differentiate between these two types of extreme values.