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A.L. McFarland, T.M. Waliczek, and J.M. Zajicek

into an Excel™ file (Microsoft Corp., Redmond, WA) and were then analyzed using SPSS ® (version 11.5; SPSS, Chicago). Statistical analysis included descriptive statistics, frequencies, correlations, and analysis of variance (ANOVA). Post hoc analyses

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Erin J. Yafuso and Paul R. Fisher

. Dissolved oxygen was measured at 4-cm depth from the surface over time (0, 30, 90, 150, 210, and 270 min). Data were analyzed by three-way analysis of variance (ANOVA) using PROC GLIMMIX, with Tukey’s honestly significant difference for mean separation in

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Alex B. Daniels, David M. Barnard, Phillip L. Chapman, and William L. Bauerle

). Data analysis. Two repeated-measures analyses of variance (ANOVA) were conducted to examine variability in substrate moisture. Together these analyses seek to describe the ways in which substrate moisture may vary among species and over time in a

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Lingdi Dong, Waltram Ravelombola, Yuejin Weng, Jun Qin, Wei Zhou, Gehendra Bhattarai, Bazgha Zia, Wei Yang, Linqi Shi, Beiquan Mou, and Ainong Shi

analysis. Data were analyzed using an analysis of variance (ANOVA) with repeated measures as described by Littell et al. (2000) . The day of salt stress was used for repeated measures. ANOVA with repeated measures was performed using PROC MIXED in SAS 9

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Michael J. Costello

) in Feb. 2000 measuring four randomly selected vines per plot at a height of 0.3 m. Yield, berry weight, °Brix, and pruning weight were analyzed by repeated measures analysis of variance (ANOVA) using a log 10 transformation and using year as the

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Martin M. Williams II, Carl A. Bradley, Stephen O. Duke, Jude E. Maul, and Krishna N. Reddy

for 72 h. Data analysis. Before analysis, data were examined with Levene’s test for homogeneity of variances ( Ott and Longnecker, 2001 ). Variances were found to be homogeneous and met analysis of variance (ANOVA) assumptions of normality. Response

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James E. Altland and Charles R. Krause

. Particle size distributions were subjected to multivariate analysis of variance (ANOVA) to determine if distributions differed as a whole and then were analyzed by univariate ANOVA within each sieve size. Means were separated within a sieve size using

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Borut Gosar and Dea Baričevič

content was meaningful to analyze for non-irrigated RFRRH treatments only, analysis of variance (ANOVA) test and Duncan's multiple range tests were used to assess the significance of the treatments. In cases in which the ANOVA test showed significant

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Brian S. Yandell

values. Most statistical methods, including analysis of variance (ANOVA), implicitly assume normality and equal variance. Miller (1997) points out that normality is not very important for ANOVA tests, although having a symmetrical distribution without

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Kristen R. Hladun and Lynn S. Adler

) and subsequent univariate analyses of variance (ANOVA) using SAS (2003; SAS Institute, Cary, NC) were used to determine the effects of pollen composition, pollen amount, and their interaction on butternut squash fruit and seed production. All data were