Abstract #301115

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JSM 2003 Abstract #301115
Activity Number: 254
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 12:00 PM to 1:50 PM
Sponsor: Section on Statistical Graphics
Abstract - #301115
Title: Fitting the Extended Generalized Lambda Distribution (EGLD) to Exercise Science Data
Author(s): Dwight J. The*+
Companies: Syracuse University
Address: 809 Hawley Ave. 2nd floor, Syracuse, NY, 13203-2925,
Keywords: goodness of fit ; K-S test ; P-P plot ; probability density function
Abstract:

Both quantitative and graphical methods were used to evaluate the fit of different distributions (Normal, Uniform, Exponential, & Extended Generalized Lambda Distribution [GLD (╏, λ2, λ3, λ4) & GBD (ß1, ß2, ß3, ß4)]) to continuously distributed, knee extension power scores from 24 participants (n=20 to 40 scores/participant). K-S test results indicate rejection (p<=0.05) of the hypothesis that data originate from the Normal, Uniform, and Exponential distributions for 0/24 (z=0.35 to 1.11; p=0.16 to 1.00), 13/24 (z=0.66 to 2.52; p=0.00 to 0.77), and 24/24 (z=3.30 to 2.14; p=0.00) participants, respectively. However, standardized and unstandardized P-P plots and Q-Q plots indicate consistent, considerable departures from normality and uniformity. Moreover, graphical and quantitative assessment of data histograms with probability density functions (constructed from both sample moments and percentiles) suggests (a) Uniform and Exponential do not provide adequate fits; (b) Normal and EGLD may provide adequate fits that are similar or dissimilar; (c) EGLD may provide a better fit than Normal; and (d) none of the aforementioned distributions may provide an adequate fit.

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