将落差数的观测结果统计分组为区间变化序列

N. Shmalko, I. Nikitin, O. Orlovtseva, I. V. Sokolov, M. F. Khayrullin
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引用次数: 0

摘要

将观察结果作为经验结果进行统计核算,需要对收集到的数据进行分组,以获得具有代表性的样本。通常,观察结果的统计分组是通过基于排序操作的分布序列来实现的。当在变分分布序列中定义经验总体的成员时,目的是揭示所研究性状的变异模式。在烘焙生产技术中,一个特殊的角色是监测加工谷物和从中获得的面粉的质量,包括当检测到缺陷时,大多数是违反水洗面筋的质量标准和数量下降。这项工作的目的是统计分组的小麦粉的数量下降的观察结果到一个区间系列的样品,酶活性降低,不符合质量标准的上限。对于所研究的指标——降数,在编制离散无间隔序列时,只能研究一个维度特征的特征及其变异系数是否符合随机变量的标准分布,在编制区间序列时,还可以研究一个经验特征分布函数。给定概率为0.95的所获得样本的代表性提供了当较大样本的平均值不超过所发现的一般平均值置信区间时的结果。在实际意义上,方差分析得到的结果对于观测值的统计核算和编制数量下降的实验数据的经验总体具有重要意义,随后将数据以分布序列表示,并获得实验中测量的特征的经验分布函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical grouping of the observation results of the fall number into the interval variation series
Statistical accounting of observations as results of experience is subjected to grouping of the collected data in order to achieve a representative sample. As a rule, statistical grouping of observation results is carried out by presenting distribution series based on a ranking operation. When defining the members of the empirical population in the variational series of distribution, the goal is to reveal the pattern of variation of the trait under study. In the technology of bakery production, a special role is assigned to monitoring the quality of the processed grain and obtained from it flour, including when defects are detected, most of which are violations of the quality standards of washed gluten and the falling number. The purpose of this work was to statistically group the results of observations of the falling number of wheat flour into an interval series for a sample with a reduced enzymatic activity that does not correspond to the upper limit of the quality standard. For the investigated indicator – the falling number, when compiling a discrete and intervalless series, you can only study the characteristics of a dimensional feature, its coefficient of variation and compliance with the standard distribution of a random variable, and when compiling an interval series, also an empirical feature distribution function. The representativeness of the obtained sample with a given probability of 0.95 provides the result when the average value for a larger sample does not go beyond the found confidence interval for the general average. In a practical sense, the obtained results of the analysis of variance are important for the statistical accounting of observations and the compilation of an empirical population of the falling number experimental data with the subsequent presentation of data in distribution series and obtaining an empirical distribution function of the characteristic measured in the experiment.
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