Saturday, February 25
PS3 Poster Session 3 and Continental Breakfast Sat, Feb 25, 8:00 AM - 9:15 AM
Conference Center AB

Statistical Comparison of Particle Size Distributions (303434)

Melinda McCann, Oklahoma State University 
*Scott J Richter, The University of North Carolina at Greensboro 

Keywords: Particle size, nonparametric, permutation test

Measuring particle size distributions (PSD) and understanding how they affect products and processes can be critical to the success of many manufacturing businesses. Techniques to measure PSD rapidly and accurately are critical tools for these industries. Thus it is important to statistically compare different techniques. A challenge is that these techniques produce data points that are estimates of distribution functions. While there are many statistical procedures available to compare two distribution functions, based on a single estimate from each, we know of no adequate methods for incorporating a sample of estimates. An extension of a nonparametric test for comparing two distribution functions based on a single estimate from each is proposed. The proposed test statistic is formed by averaging test statistics of all possible pairs of data points. The reference distribution is then obtained by randomly permuting the empirical distribution functions across the two treatments and calculating the resulting summary test statistic. The method is applied to data from an industrial application. .