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Coefficient of variation in field experiments, and yardstick thereof - Anempirical study

机译：野外实验的变异系数及其准绳-实证研究

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The experimental data provide information on controlled (treatment effect) and uncontrolled variation. The uncontrolled variation is expressed as experimental error, which could be quantified as an estimate called 'coefficient of variation (CV)'. Besides, fertility variation among experimental units (plots), the factors contributing toward uncontrolled variation are climatic and experimental. Therefore CV of field experiments varies with the situation. Lower magnitude of CV is the reflection of reliability (precision) of the experimental results. The acceptable range of CV advocated by various workers is based on the experience with very limited number of experiments. There is a need to develop a yardstick (critical value) for CV based on theory and also on a large number of experiments conducted under different situations. The present paper deals with this aspect. Johnson and Welch reported that for a normal distribution, the ratio of mean to standard deviation should be of the order of 3 or more. Further, they mentioned that 33 percent has often been stated as the permissible upper fiducial limit of CV. Tyagi et al. and Patel el al. pointed out that CV obtained for the crops under study was lound to be considerably higher than those reported from the uniformity trials. They stated that the yardstick for accepting experimental results should be worked out using CV observed in the experiments rather than in the uniformity trials. Bajpai and Nigam suggested at working rule for deciding the value of W2 (weight corresponds to precision of the experiment) and developed an index to evaluate agricultural field experiments statistically. Gomez and Gomez reported that CV varies greatly with the type of experiment, the crop grown and the character measured. They opined that the acceptable range of CV is 6 to 8 percent for varietal trials, 10 to 12 percent for fertilizer trials and 13 to 15 percent for insecticidal and herbicidal trials on rice. No other information (except reviewed and reported here), is available in the literature on the yardstick of CV for field experiments on crops.
机译：实验数据提供了有关受控（治疗效果）和非受控变异的信息。不受控制的变化表示为实验误差，可以将其量化为称为“变化系数（CV）”的估计值。此外，实验单位（地块）之间的生育率变化，导致不受控制的变化的因素是气候和实验因素。因此，现场实验的简历随情况而变化。较低的CV值反映了实验结果的可靠性（精度）。各种工作人员提倡的CV可接受范围是基于非常有限的实验经验。有必要根据理论以及在不同情况下进行的大量实验来制定CV的标准（临界值）。本论文涉及这一方面。 Johnson和Welch报告说，对于正态分布，均值与标准偏差之比应为3或更大。此外，他们提到33％通常被称为CV的允许基准上限。 Tyagi等。和Patel al。指出，所研究作物的CV值要远远高于均匀性试验报告的CV值。他们表示，应该使用在实验中观察到的CV来制定接受实验结果的标准，而不是在均匀性试验中。 Bajpai和Nigam建议在工作规则中确定W2的值（权重对应于实验的精度），并开发了一个指标，用于对农业田间试验进行统计学评估。戈麦斯（Gomez）和戈麦斯（Gomez）报告说，CV随实验类型，作物生长和所测特性而有很大差异。他们认为，水稻品种的CV可接受范围为6％至8％，肥料试验的CV范围为10至12％，杀虫和除草试验的CV范围为13至15％。在关于作物田间试验的简历标准方面，文献中没有其他信息（此处未进行复述和报道）。

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