EL-Taweel,, A. (2004). USING POWER FUNCTION OF THE ANALYSIS OF VARIANCE TEST IN WHEAT EXPERIMENTS. Journal of Plant Production, 29(3), 1035-1049. doi: 10.21608/jpp.2004.238513
A. M. S. A. EL-Taweel,. "USING POWER FUNCTION OF THE ANALYSIS OF VARIANCE TEST IN WHEAT EXPERIMENTS". Journal of Plant Production, 29, 3, 2004, 1035-1049. doi: 10.21608/jpp.2004.238513
EL-Taweel,, A. (2004). 'USING POWER FUNCTION OF THE ANALYSIS OF VARIANCE TEST IN WHEAT EXPERIMENTS', Journal of Plant Production, 29(3), pp. 1035-1049. doi: 10.21608/jpp.2004.238513
EL-Taweel,, A. USING POWER FUNCTION OF THE ANALYSIS OF VARIANCE TEST IN WHEAT EXPERIMENTS. Journal of Plant Production, 2004; 29(3): 1035-1049. doi: 10.21608/jpp.2004.238513
USING POWER FUNCTION OF THE ANALYSIS OF VARIANCE TEST IN WHEAT EXPERIMENTS
Cent. Lab. for Design and Stat. Analysis, A. R. C. Giza, Egypt.
Abstract
The uniform plots and blocks are very importanllo lesl and deleel !he !rue
differences between experimental units in field experiments (treatments). The size of block and number of plots per block and number of samples per plot depends upon the variability of the sample, which depends upon the degree of soil homogeneity. Two uniformity trials were applied at sids Agricultural research station Bein Suef governorate during 2001/2002 and 2002 seasons. Sids 7 variety was sown in rows 3m long and 20 cm apart in 8 strips with 200 rows for each strip. Each trial for each season was assigned in randomized Complete Block design (RCBD) in four replications. Data were analyzed with sub sampling method in different number of experimental units, different number of sample units and different plot and block sizes. To determine optimum combinations of sampling units, experimental units, block and plot sizes to detect the true effect of treatments, the power function of the analysis of variance 02 was used according to Dixon and Massey (1951). The suggestion in this study is the changing of the number of samples and number of experimental units, followed by changing in the plot and the block sizes. This change will be followed by changing in the power function of the analysis of variance (02).
Results of comparing calculated and tabulated power function of the analysis 02 cleared that the power increased for all combinations as a result of increasing sample units. Increasing number of experimental units per block led to a decrease in number of sample units and increases the power function of the analysis 02 for all combinations. Increasing number of experimental units to ten in each block, the number of sample unit starts to be constant being seven. Results also indicated that increasing sample units clearly decreased sampling errors and this decrease became slight up to the combinations, which were selected by the power function of the analysis of variance 02 and started to be constant.
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