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The Significance Testing of a Skewed Color-Imaging Data Set

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In color-imaging science researchers frequently conduct experiments that are evaluated by measuring a number of ΔE values. Often the effect of various experimental parameters is evaluated by comparing the means of two or more sets of ΔE values. Frequently, a t-test is used but correct application of the t-test requires that a number of assumptions (such as the data being normally distributed or the sample size is big enough) are satisfied. In this article, an improved T statistic has been used in a case study where the data are skewed and do not have a normal distribution while at the same time the sample size is small. The importance of this assumption comes to mind when we realize that most of the derived data from the color-imaging science are not applicable for t-test because of not following a normal distribution.

Document Type: Research Article

Publication date: January 1, 2011

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, and a vibrant interactive papers session. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper presentation.

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