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Peng Shi, Yong Wang, Dapeng Zhang, Yin Min Htwe, and Leonard Osayande Ihase

-related traits among these germplasms were observed and then analyzed using cluster, analysis of variance (ANOVA), correlation, path, and regression analysis, respectively. Furthermore, FOC prediction was constructed and validated for germplasm evaluation. The

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Manjul Dutt and Robert Geneve

and radicle. Cumulative length in pixels was converted to mm using a standard calibration image. Growth rate was calculated as the slope of the linear regression of seedling length measured after initiation of radicle protrusion for germinated

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Alexander R. Kowalewski, Brian M. Schwartz, Austin L. Grimshaw, Dana G. Sullivan, and Jason B. Peake

and Longnecker, 2001 ). A series of regression analysis for various leaf morphology, density, and color parameters across the final percent green turf color observed at the conclusion of the 6-week traffic period were conducted to determine whether

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Anne M. Lockett, Dale A. Devitt, and Robert L. Morris

multiple regression analysis. Multiple regressions were performed in a backward stepwise manner, deleting terms that occurred when P values for the t test exceeded 0.05. To eliminate multicollinearity, variance inflation factors (VIF) were calculated

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L. Carolina Medina, Jerry B. Sartain, and Thomas A. Obreza

that the N release curve with time for a specific SRF product can be predicted based on the accelerated laboratory extraction data. Nonlinear regression techniques are used to establish this relationship. The first step is to fit nonlinear regression

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Steven J. MacKenzie, Craig K. Chandler, Tomas Hasing, and Vance M. Whitaker

selected for inclusion in the model. Subsequently, mean solar radiation values over intervals from 1 to 21 d were evaluated in a multiple regression analysis along with the mean 8-d temperature before harvest. Temperature and solar radiation data were

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Xiao-li Li and Yong He

multivariate analysis technique in chemometrics ( Gomez et al., 2006 ; Lammertyn et al., 1998 ; Min and Lee, 2005 ; Zou et al., 2007 ). Compared with multiple linear regression (MLR), the advantage of PLS is that it is a bilinear modeling method in which the

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Monica Ann Pilat, Amy McFarland, Amy Snelgrove, Kevin Collins, Tina Marie Waliczek, and Jayne Zajicek

(version 17.0™; IBM Corp., Armonk, NY). Descriptive statistics analyzed the vegetation cover of each MSA. A linear regression analysis was used to calculate the extent to which relative humidity, temperature, ozone, particulate matter, and ethnicity

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Winston Elibox and Pathmanathan Umaharan

studied in Trial 1 and vase life as determined by the time taken to deterioration. The association between morphophysiological characteristics and vase life was assessed using Pearson's product moment correlation ( NCSS, 2001 ). Multiple regression

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Joanna Brown, Gregory Colson, Claire B. de La Serre, and Nicholas Magnan

; StataCorp, College Station, TX). To estimate demographic differences between the TLW and PPC programs, two-sided t tests were used. To estimate demographic correlates of outcomes at baseline, multiple linear regressions were used. To estimate overall