The utility of Covariance Assumption Test – ANOVA approach and relative error of Cell Number Estimation by simulation

Numeric processing on analysis and diagnostic dataset of relationship between spectrum light and cell particles of S cerevisiae was performed to analyze the covariance on regression assumption and relative error of cell number estimation to a model. The one model should be chosen and the relationship of that i.e. the model for standard curve on turbidimetry. Under Windows 10 OS the application with using DosBox 0.74 were used for Biology system. This document consists of utility of covariance assumption test, simulation, and the computation proof by Excel in Windows OS.

本研究针对酿酒酵母（Saccharomyces cerevisiae）的光谱光信号与细胞颗粒间关联关系的分析诊断数据集开展数值处理，旨在分析回归假设下的协方差特性，以及基于预测模型的细胞数量估算相对误差。需从中选取适配模型，并明确其内在关联关系，即比浊法标准曲线对应的预测模型。本研究依托Windows 10操作系统，借助搭载DosBox 0.74的应用程序完成生物学系统相关计算。本数据集文档涵盖协方差假设检验、模拟仿真的实现方法，以及基于Windows操作系统下Excel完成的计算验证流程。