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Análise estatística do ensaio de variedades de café

机译:咖啡品种测试的统计分析

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This paper describes the statistical analysis of a varietal trial with two unusual characteristics : (i) The plant (coffee) is one of those which show strong maxima and minima of production in alternate years. This phenomenon must be prevented from masking or biasing the other varietal comparisons in which we are interested. (ii) The design of the experiment is systematic. It was laid down in Campinas, Brazil, in 1933 at a time when the principles of randomisation were not so widely known as they are today. THE EXPERIMENT AND DATA. Six varieties are compared, denoted by A B C D E and F (see page 104). They are planted in thirty rows, each with 50 plants, according to the systematic design : A B C D E F A B C D E F A B C D E F A B C D E F A B C D E F Data for twelve years are available in quadro 1 but those of the small and irregular yields in the first two years were discarded. The mean yields of the remaining ten years (1935-1946) appear by figure 1 to be fairly regular and consistent in their behaviour. Most of the plants, but by no means all, showed their maxima in the even years. STATISTICAL ANALYSIS. The quantity of primary interest is the mean yield over the whole period. It is essential that these means should be based (as here) on an even number of years in order to eliminate, from their comparisons, the effect of the alternations of maxima and minima. The magnitude of the oscillation is conveniently measured by total of even years minus total of odd years. Finally we need a linear function of the annual yields for measuring secular trend in order to discriminate varieties which are slowly gaining on the others. The usual linear orthogonal polynomial (with coefficients -9, -7, -5, etc.) is unsuitable because it is not independent of the component of oscillation. A suitable function is obtained instead by using the coefficients -2 -2 -1 -1 0 0 +1 +1 +2 +2. The coefficients of the three linear functions thus defined are set out in quadro 2 (page 107), where it will be verified that they are mutually orthogonal. The effect of the heterogeneity of the soil is as far as possible eliminated (separately for the three functions) by an analysis of covariance, using the number of the row (1-30) as the concommitant observation. A simple linear regression formula is however inadequate. The regressions were taken to the fifth degree by means of orthogonal polynomials. Since the "between varieties" contribution must be removed from the sums of squares and products, the regression coefficients are no longer independently obtainable. It is found however that the normal equations fall into two sets, one yielding the regression coefficients of odd degree and the other those of even degree. Consequently the use of orthogonal polinomiais still effects a considerable saving of work. The computations are set out in full in quadro 3 and in abbreviated form in quadro 4 and 5 for the total, the oscillation and the trend respectively. (Note that the comma indicates the decimal point.) We find that a quadratic regression is adequate for the first and cubic regressions for the others. For the sake of uniformity, a cubic regression was used in every case. The residuals found by subtracting the varietal means from the rows are plotted in figures 2a, 3 and 4a. respectively, together with the regression curves and the 2.5% control limits. These control charts suggest that it is not unreasonable to suppose that the remaining variation is random. Next we use the regression formulae to correct the varietal means. The approximate 80% fiducial intervals of the mean annual yields (kg per row) and the rate of increase of yield (kg per row per year per year) are shown in figures 2b and 4b respectively. In the case of the component of oscillation, the analysis of covariance failed to show the slightest suggestion of differences between varieties. DISCUSSION. An examination of the regressions on number of row reveals the interesting fact that the more fertile portions of the field produce lower yields in the odd years than the less fertile portions. The reason is presumably that the heavier yields in the even years, by exhausting the plant, depress the yields in the following years. The major differences between varietal means over the ten years were sufficiently clear even before the analysis though some of the adjustments are appreciable. A striking fact is that, although there are big general differences between varieties, there are no significant differences between them in respect of the amplitude of oscillation. In other words, the increment of yield in the better varieties is obtained equally in odd and even years. In spite of the large component of oscillation, it is possible to discriminate varieties in respect of their rate of increase of yield (figure 4b). CONCLUSIONS. (i) The extra difficulty introduced by the strong alternations of yield from year to year can be solved b y the choice of suitable orthogonal functions of yearly
机译:本文描述了具有两个不同特征的品种试验的统计分析:(i)植物(咖啡)是在交替年份中表现出极大的最大值和最小值的植物之一。必须防止这种现象掩盖或偏离我们感兴趣的其他品种比较。 (ii)实验的设计是系统的。它是在1933年在巴西坎皮纳斯(Campinas)铺设的,当时的随机化原理并不像今天这样广为人知。实验和数据。比较了六个品种,分别用A B C D E和F表示(请参见第104页)。根据系统设计,将它们分为30行种植,每行50株植物:Quadro 1提供了十二年的数据,但前两年单产和不规则产量的数据都被丢弃了。由图1可以看出,剩余十年(1935-1946年)的平均产量相当规律且行为一致。大多数植物,但绝不是全部,在偶数年中都显示出最大值。统计分析。主要利息的数量是整个期间的平均收益率。为了从比较中消除最大值和最小值交替产生的影响,必须将这些方法以偶数年为基础(如此处所示)。可以通过偶数年的总和减去奇数年的总和来方便地测量振荡的幅度。最后,我们需要年产量的线性函数来衡量长期趋势,以区分正在逐渐增加的品种。普通的线性正交多项式(系数为-9,-7,-5等)是不合适的,因为它与振荡分量无关。而是通过使用系数-2 -2 -1 -1 0 0 +1 +1 +2 +2获得合适的函数。这样定义的三个线性函数的系数在quadro 2(第107页)中列出,在那里将验证它们是相互正交的。通过使用行数(1-30)作为伴随观测,通过协方差分析,尽可能地消除了土壤异质性的影响(分别针对三个功能)。但是,一个简单的线性回归公式是不够的。通过正交多项式将回归降至第五级。由于必须从平方和乘积之和中删除“变体之间”的贡献,因此不再可以独立获得回归系数。但是,发现正规方程分为两组,一组产生奇数级的回归系数,另一组产生偶数级的回归系数。因此,使用正交策略仍然可以节省大量的工作。计算分别以总和,趋势和趋势的形式在第3阶段中完整列出,并在第4和5阶段中以缩写形式列出。 (请注意,逗号表示小数点。)我们发现二次回归对于第一个回归是足够的,而其他三次回归就足够了。为了统一起见,在每种情况下均使用三次回归。图2a,3和4a绘制了通过从行中减去变量平均值而发现的残差。以及回归曲线和2.5%的控制极限。这些控制图表明,假设剩余的变化是随机的并不是没有道理的。接下来,我们使用回归公式来校正品种平均值。图2b和图4b分别显示了平均年产量(每行千克)和年增长率(每年每行千克)的大约80%的基准间隔。就振荡成分而言,协方差分析未能显示出品种之间差异的丝毫暗示。讨论。对行数回归的检验揭示了一个有趣的事实,即在奇数年中,田间肥沃的部分比肥沃的部分更少的产量较低。原因大概是,由于连年累累,单株植物的精疲力竭降低了单株的产量。尽管有一些调整是可观的,但即使在分析之前,十年间品种平均值之间的主要差异也已经足够清楚。一个引人注目的事实是,尽管品种之间存在较大的一般差异,但就振荡幅度而言,它们之间没有显着差异。换句话说,更好的品种的产量增加在奇数年和偶数年均能获得。尽管振荡的成分很大,但仍可以根据品种的增产率来区分品种(图4b)。结论。 (i)通过逐年选择合适的正交函数可以解决逐年高产交替带来的额外困难

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    《Bragantia》 |1949年第8期|共21页
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