Analysis of Residuals for the Elimination of total Suspended Solids Simulation of wastewater through Rotating Biological Contactor

M. G. Talpur, M. R. Daudpoto, A. Kakar, M. I. Wassan, A. Shaikh
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Abstract

Increased attention towards substitute water resources has become unavoidable, as the world’s freshwater supply becomes gradually scarcer. Reuse of Greywater is a hopeful alternative water source for non-potable uses, which could be exploited on a continuous basis and treated. Getting average removal% of Total Suspended Solids from greywater through Rotating Biological Contactor following experiment was conducted to evaluate the significance Hydraulic Retention Time with numbers of discs. Consequences reveal that linear as well as quadratic estimate of HRT and number of discs have are highly significant effect as their corresponding p-values are even less than 0.01.By using coefficients of the table the regression equation is Removal = Removal% = -26.74 + 20.14 Time + 1.253 Disc, where the sample standard deviation is 4.82. Lack of fit of the equation is insignificant i.e. 0.155, which implies that the regression equation is fit for prediction. The probability plot of the residuals is roughly straight which demonstrate that errors distributions are around normal. Furthermore, Residual plot shows the linearity assumption appear to be met with constant standard deviations. Histogram of Residuals make obvious normality assumptions as the plot resembles an example of a sample from a normal distribution centered at zero and normally and independently distributed NID (0, σ2) assumptions on errors are accomplished as standardized residuals are approximately normal with mean zero and unit variance.
旋转生物接触器模拟废水去除总悬浮物的残留量分析
随着世界淡水供应逐渐减少,对替代水资源的更多关注已不可避免。灰水的再利用是一种有希望用于非饮用用途的替代水源,可以持续开发和处理。通过实验,得到了旋转生物接触器对灰水中总悬浮物的平均去除率%,以评价水力停留时间与圆盘数的关系。结果显示,HRT和椎间盘数目的线性和二次估计具有非常显著的影响,其对应的p值甚至小于0.01。利用表中的系数,得到回归方程为:Removal = Removal% = -26.74 + 20.14 Time + 1.253 Disc,其中样本标准差为4.82。方程的拟合缺失不显著,即0.155,这意味着回归方程适合预测。残差的概率图大致为直线,表明误差分布接近正态分布。此外,残差图显示线性假设似乎满足恒定的标准偏差。残差直方图做出了明显的正态性假设,因为该图类似于一个以零为中心的正态分布的样本,正态和独立分布的NID (0, σ2)对误差的假设是完成的,因为标准化残差近似正态,平均值为零,单位方差。
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