Testing the hypothesis of the normality of the falling number of oatmeal in small samples

N. A. Shmalko, I. A. Nikitin, D. A. Velina, L. F. Ponomareva, S. E. Terentev
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Abstract

Verification of the hypothesis of the normality of small samples is required to establish whether the empirical distribution obtained belongs to the theoretical distribution. The condition for testing the hypothesis of normality for a set of small independent samples is the presence of a sufficient number of them with the same volume. In this case, it is possible to test the hypothesis of the normality of the general aggregates from which the studied samples were taken, assuming that the parameters of these aggregates have different values. When testing the hypothesis of normality for a large number of small samples, only one value of the first, second, etc. measurements is randomly selected from each sample, thereby allowing simplification and random selection of data. The object of this study is small samples of the falling number of oat flour used in bakery production in the development of bakery products. The purpose of this work was to test the hypothesis of normality for small samples of the experiment using the nonparametric criterion of agreement ω2 of the smallest of each of the four definitions of the incidence number, since rounding the values of direct measurements excludes the random nature of the quantity or its normal distribution in favor of a uniform one. It was found that at a significance level of p = 0?05, the table value (nω2)1-p is greater than the calculated value of nω2 for all four definitions, hence the hypothesis of the normal distribution of small samples for all four definitions (as random variables) of the falling number of oatmeal does not deviate. The results obtained in this work are consistent with the generally accepted classical concepts of testing the statistical hypothesis of the normal distribution of samples. The statistical method provides sufficient accuracy of the studied indicator in technical systems and does not require the synthesis of a statistical criterion to test the hypothesis of the normality of small sample.
检验小样本中燕麦片数量下降的正态性假设
为了确定得到的经验分布是否属于理论分布,需要对小样本正态性假设进行验证。检验一组小的独立样本的正态性假设的条件是存在足够数量的相同体积的小样本。在这种情况下,假设这些聚集体的参数具有不同的值,就有可能检验所研究样本所取自的一般聚集体的正态性假设。在对大量小样本进行正态性假设检验时,从每个样本中随机选取第一、第二等测量值中的一个值,从而简化和随机选择数据。本研究的对象是在烘焙产品的开发中,用于烘焙生产的燕麦面粉数量下降的小样本。这项工作的目的是使用四种发生率定义中每一种最小值的非参数一致性ω2标准来检验实验小样本的正态性假设,因为直接测量值的四舍五入排除了数量的随机性质或其正态分布的均匀性。结果发现,在p = 0?05时,四种定义的表值(nω2)1-p均大于nω2的计算值,因此四种定义(作为随机变量)的燕麦片下降数的小样本正态分布假设不偏离。在这项工作中得到的结果与普遍接受的经典概念是一致的,即检验样本正态分布的统计假设。统计方法在技术系统中为所研究的指标提供了足够的准确性,并且不需要综合统计标准来检验小样本正态性假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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审稿时长
8 weeks
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