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720 COLOR SENSITOMETRY June
reduction of this particular source of variation to the minimum value that is economically practical.
Variations in sensitometric exposure cannot be isolated on finished sensitometric strips, but photometric methods can be used to arrive at an independent check on the magnitude of such variations.
On the other hand, there is no completely satisfactory procedure by which variations in film or processing can be independently studied. The difficulties of separating these two factors have already been considered in Section III. The best that can be done is to study one of the components of variation under conditions that make the remaining components relatively small. For example, a single test of film variability can be made by exposing sensitometric strips as closely as possible at the same time on a carefully controlled sensitometer, and then processing all of the strips in random sequence at the same time. Where repeated tests of this kind are required, it will be desirable to keep process variations small, because differences in film characteristics vary with process changes.
Multiple Factor Experiments
Statistical methods29 are available for the treatment of more complicated experiments in which two or more factors are separated and evaluated in the same group of experiments. However, in applying such methods to problems involving film and processing variations, one must be sure to exclude assignable causes of variation resulting from "keeping" changes in the film during the intervals between manufacture and exposure and between exposure and processing. This is very difficult in practice, and multiple factor experiments have therefore been little used in color sensitometry.
As an illustration of a somewhat different use of such multiple factor experiments, consider the problem of maintaining two or more densitometers so that six different test operators will be able to obtain essentially the same densitometric measurements on all parts of the scale of a sensitometric strip. Each test operator would be asked to make density measurements on several sensitometric strips using both densitometers. The resulting data could be studied by variance analysis29 to see whether significant differences existed between the results from Operator A and Operator D, or between Densitometer No. 1 and Densitometer No. 2.
Statistical Methods of Data Presentation
Statistical methods are most efficient when used to help interpret the results of experiments which have been properly designed. Several