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Christopher C. Mundt

wise decision in my opinion. This book is largely organized around mathematical models. It also contains a wealth of information on modern statistical approaches to data analysis. Thus, the publication provides a comprehensive reference for those

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Lydia E. Wahba, Nor Hazlina, A. Fadelah and Wickneswari Ratnam

, their corresponding accession numbers, and classification. Morphological data analysis. All plants were assessed for 21 morphological traits, all of which were referred by Sheehan and Sheehan (1994) : plant height, root type, leaf type, leaf height

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Yohei Kurata, Tomoe Tsuchida and Satoru Tsuchikawa

acidity determinations. Table 1. The statistical data of soluble solids concentration (SSC) and acidity in samples of 70 commercial white grapefruit harvested in Florida. Data analysis. In the TOF-NIRS measurement, the cross-correlation function was used

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Elzbieta U. Kozik and Todd C. Wehner

constituted the plot contained three plants of each parent, six F 1 plants, six BCP 1 plants, six BCP 2 /BCP 3 plants, and 30 F 2 plants. Data analysis. For purposes of data analysis, plants rated 0 to 6 were considered to be resistant, and those

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Danielle E. Hammond, Amy L. McFarland, Jayne M. Zajicek and Tina M. Waliczek

questionnaires received. Two responses were from individuals outside the United States and were removed from data analysis. Thus, 140 responses were used for the final data analysis. According to Cohen (1992) , 140 responses should yield a power of 0.80 with a

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Michael W. Smith and William D. Goff

analyzed using chi-square (PROC FREQ in SAS 9.4 software; SAS Institute, Cary, NC). Data analysis included budwood treatments and rootstock treatments pooled over rootstock planting location. Data analysis also included plant location pooled over budwood

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Sai Xu, Huazhong Lu and Xiuxiu Sun

litchi samples was determined as described by previous research ( AOAC Official Method 942.15, 1965 ; Jiang et al., 2004 ). The TA was defined as the percentage of citric acid determined by titration with 0.1 M NaOH. Data analysis methods. The linear

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Gayle M. Volk, Christopher M. Richards, Adam D. Henk, Ann Reilley, Diane D. Miller and Philip L. Forsline

Excoffier, L.G.L. Schneider, S. 2005 Arlequin ver. 3.0: An integrated software package for population genetics data analysis Evol. Bioinform. Online 1 47 50 < http://lgb.unige.ch/arlequin/ > Forsline, P.L. Aldwinckle, H.S. Dickson, E.E. Hokanson, S.C. 2003

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Dilma Silva, Donald Cox and Richard C. Beeson Jr

yield data were arcsin square root-transformed for data analysis ( Palta, 2003 ). Data analysis was accomplished using SAS (Version 9.1; SAS Institute, Cary, NC). Table 1. Root ball volume, plant age, and substrate/soil type for each species used to

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Brian S. Yandell

can be quite harmful. For numerous examples in a variety of settings, see Wainer (1984) and the books of Edward Tufte (1983 , 1990 , 1997 ). The classic How to Lie with Statistics by Huff (1993) contains many examples of poor data analysis